Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As demand for AI continues to accelerate, how to scale and improve engineering productivity become one of the company’s most strategic challenges.
We are looking for an experienced Technical Program Manager to help lead the cross functional team programs to ensure we have the right strategy and execution to deliver what is needed to scale engineering. This role will work directly with different engineering teams, IT, Infrastructure, Security, Operations, and executive leadership to maximize our engineering productivity so that we can our customer demands without linearly increasing the team size.
Responsibilities
Be responsible for defining and delivering important programs with broad organizational, business and technical impact in Dev Productivity domain.
Provide cross-functional leadership with Engineering and Product Management, and inter/intra team communications to deliver outstanding program outcomes.
Bring strong, data-driven and strategic technical judgment to decisions.
Be hands-on, working closely with Software Engineers and Product Managers to design, build, and deliver the next generation of Snowflake services and apps.
Amplify your impact by educating and mentoring the TPM and Engineering communities on program management best practices.
Identify opportunities to improve execution of the organization as a whole, to increase engineering productivity through tools and light-weight processes. (Snowflake happens to have a nice data platform to use).
Skills & Qualifications
5+ years of demonstrated industry experience and expertise leading medium to large complex engineering projects in current cloud technologies.
Ability to thrive and succeed in a dynamic environment not slowed down by ambiguity or competing priorities.
Experience working cross functionally with engineering, product management, and other functions involved in the product life cycle.
Strong program management skills with technical and business acumen.
Effective verbal and written communication and presentation skills, with the ability to interact with technical and non-technical groups.
Excellent analytical, problem-solving, consultation and organizational skills.
Preferred Skills & Qualifications
BS/MS/PhD degree in Computer Science, Engineering, or related fields or equivalent practical experience (e.g. familiarity with SQL, Python, Data).
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs demand for AI continues to accelerate, how to scale and improve engineering productivity become one of the company’s most strategic challenges.\n\nWe are looking for an experienced Technical Program Manager to help lead the cross functional team programs to ensure we have the right strategy and execution to deliver what is needed to scale engineering. This role will work directly with different engineering teams, IT, Infrastructure, Security, Operations, and executive leadership to maximize our engineering productivity so that we can our customer demands without linearly increasing the team size.\n\nResponsibilities\n\n - Be responsible for defining and delivering important programs with broad organizational, business and technical impact in Dev Productivity domain.\n\n - Provide cross-functional leadership with Engineering and Product Management, and inter/intra team communications to deliver outstanding program outcomes.\n\n - Bring strong, data-driven and strategic technical judgment to decisions.\n\n - Be hands-on, working closely with Software Engineers and Product Managers to design, build, and deliver the next generation of Snowflake services and apps.\n\n - Amplify your impact by educating and mentoring the TPM and Engineering communities on program management best practices.\n\n - Identify opportunities to improve execution of the organization as a whole, to increase engineering productivity through tools and light-weight processes. (Snowflake happens to have a nice data platform to use).\n\nSkills & Qualifications\n\n - 5+ years of demonstrated industry experience and expertise leading medium to large complex engineering projects in current cloud technologies.\n\n - Ability to thrive and succeed in a dynamic environment not slowed down by ambiguity or competing priorities.\n\n - Experience working cross functionally with engineering, product management, and other functions involved in the product life cycle.\n\n - Strong program management skills with technical and business acumen.\n\n - Effective verbal and written communication and presentation skills, with the ability to interact with technical and non-technical groups.\n\n - Excellent analytical, problem-solving, consultation and organizational skills.\n\nPreferred Skills & Qualifications\n\n - BS/MS/PhD degree in Computer Science, Engineering, or related fields or equivalent practical experience (e.g. familiarity with SQL, Python, Data).\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"024f1401-76cc-43fa-9338-cc3262a793d3","title":"System Software Engineer (Embedded)","department":"Hardware Departments","team":"Systems","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-02-17T20:54:33.551+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/024f1401-76cc-43fa-9338-cc3262a793d3","applyUrl":"https://jobs.ashbyhq.com/cerebras/024f1401-76cc-43fa-9338-cc3262a793d3/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As part of the Embedded Software team, you will help build the critical software foundation that powers the Cerebras Wafer Scale Engine (WSE)—the world’s largest AI processor. Our team owns a diverse range of embedded and system level components that enable the WSE to operate reliably at scale, including microcontroller firmware, wafer level monitoring logic, system administration services, and the Linux platform and BSP layers that keep the entire system running smoothly.
This role exists at the intersection of embedded systems, platform engineering, and distributed system enablement. As our technology and deployments continue to scale, we are expanding the team with versatile engineers eager to work across multiple layers of the software stack. You will help build administrative services that connect the WSE’s system software to cluster-level orchestration, collaborate closely with hardware and ASIC teams, and contribute to the robustness, visibility, and operability of our next-generation AI systems.
Responsibilities
Develop administrative software that enables communication between system-level software and cluster-level control layers.
Provide and extend Linux BSP support, ensuring reliability and maintainability of system level platform components.
Collaborate across teams to gather requirements, define scope, plan milestones, and deliver high-quality implementations.
Work closely with datacenter operations and debug teams to diagnose system level issues, root cause failures, and implement fixes.
Partner with hardware and ASIC teams to design and implement software that monitors system hardware and wafer level behavior.
Contribute to improving system reliability, observability, and long-term maintainability across layers of the embedded stack.
Participate in code reviews, design discussions, and cross-team technical planning.
Skills & Qualifications
Minimum Qualifications
Bachelor’s degree in computer engineering, Electrical Engineering, Computer Science, or related field.
5+ years of experience in building production-quality software in C++ or Golang.
Solid understanding of embedded systems fundamentals or system hardware interactions.
Experience working in cross-functional engineering environments.
Preferred Qualifications
Master’s degree in computer engineering, Electrical Engineering, Computer Science, or related field.
Exposure to distributed systems, cluster-level orchestration, or datacenter environments.
Familiarity with Linux kernel concepts, device drivers, or BSP layers.
Experience debugging hardware/software interactions using tools such as logic analyzers, JTAG, or profiling/tracing frameworks.
Experience contributing to system monitoring, observability tooling, or hardware level telemetry pipelines.
The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role \n\nAs part of the Embedded Software team, you will help build the critical software foundation that powers the Cerebras Wafer Scale Engine (WSE)—the world’s largest AI processor. Our team owns a diverse range of embedded and system level components that enable the WSE to operate reliably at scale, including microcontroller firmware, wafer level monitoring logic, system administration services, and the Linux platform and BSP layers that keep the entire system running smoothly. \n\nThis role exists at the intersection of embedded systems, platform engineering, and distributed system enablement. As our technology and deployments continue to scale, we are expanding the team with versatile engineers eager to work across multiple layers of the software stack. You will help build administrative services that connect the WSE’s system software to cluster-level orchestration, collaborate closely with hardware and ASIC teams, and contribute to the robustness, visibility, and operability of our next-generation AI systems. \n\nResponsibilities \n\n - Develop administrative software that enables communication between system-level software and cluster-level control layers. \n\n - Provide and extend Linux BSP support, ensuring reliability and maintainability of system level platform components. \n\n - Collaborate across teams to gather requirements, define scope, plan milestones, and deliver high-quality implementations. \n\n - Work closely with datacenter operations and debug teams to diagnose system level issues, root cause failures, and implement fixes. \n\n - Partner with hardware and ASIC teams to design and implement software that monitors system hardware and wafer level behavior. \n\n - Contribute to improving system reliability, observability, and long-term maintainability across layers of the embedded stack. \n\n - Participate in code reviews, design discussions, and cross-team technical planning. \n\nSkills & Qualifications \n\nMinimum Qualifications \n\n - Bachelor’s degree in computer engineering, Electrical Engineering, Computer Science, or related field. \n\n - 5+ years of experience in building production-quality software in C++ or Golang. \n\n - Solid understanding of embedded systems fundamentals or system hardware interactions. \n\n - Experience working in cross-functional engineering environments. \n\nPreferred Qualifications \n\n - Master’s degree in computer engineering, Electrical Engineering, Computer Science, or related field. \n\n - Exposure to distributed systems, cluster-level orchestration, or datacenter environments. \n\n - Familiarity with Linux kernel concepts, device drivers, or BSP layers. \n\n - Experience debugging hardware/software interactions using tools such as logic analyzers, JTAG, or profiling/tracing frameworks. \n\n - Experience contributing to system monitoring, observability tooling, or hardware level telemetry pipelines. \n\nThe base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"0322249e-e2d4-4e0a-9133-6f173000173a","title":"Manufacturing Linux Network Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-05-01T16:11:29.007+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/0322249e-e2d4-4e0a-9133-6f173000173a","applyUrl":"https://jobs.ashbyhq.com/cerebras/0322249e-e2d4-4e0a-9133-6f173000173a/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are seeking an experienced Manufacturing Linux / Network Engineer to design, implement, and maintain robust IT and network infrastructure across our manufacturing facilities. The ideal candidate brings deep expertise in Linux systems administration (Red Hat / Rocky Linux), network security (Palo Alto firewalls), storage infrastructure, CI/CD pipelines (Jenkins), and infrastructure automation (Ansible). This role sits at the intersection of enterprise IT and plant-floor operations, and is critical to delivering the high availability, security, and performance that modern manufacturing environments demand.
Design, deploy, and maintain LAN/WAN network infrastructure spanning manufacturing plants, warehouses, cloud providers, and corporate sites.
Implement and manage high-speed core switching at 10G and 100G using Arista, Juniper, and other enterprise switching platforms; ensure scalable, resilient fabric design.
Configure, troubleshoot, and optimize Layer 2/3 networking (LACP, VLANs, BGP) and security controls (Palo Alto firewalls, VPNs, NAC, IDS/IPS); manage ISP link failover and path redundancy.
Deploy, configure, and maintain Linux servers (Red Hat / Rocky Linux) using automation tools including Ansible, MAAS, Foreman, and custom scripting to ensure consistent, repeatable provisioning.
Monitor network and system performance — uptime, latency, bandwidth utilization, and capacity — across all sites; proactively detect and resolve issues before they impact
Design and maintain redundancy, failover, QoS, and traffic engineering strategies to support 24/7 manufacturing operations and minimize unplanned downtime.
Manage structured cabling, Wi-Fi 6/6E wireless infrastructure, and ruggedized networking hardware suited for plant-floor environments.
Partner with engineering, automation, OT, and IT security teams to ensure secure and reliable connectivity for production and operational systems.
Lead and contribute to greenfield and brownfield IT/OT modernization projects, including network redesigns for new equipment rollouts and facility expansions.
Own network documentation including topology diagrams, IP address management (IPAM), and standard operating procedures; keep them current as infrastructure evolves.
Provide Tier 2/3 support for network and Linux system incidents at manufacturing sites; participate in on-call rotation for production-critical issues.
Bachelor’s degree in Computer Science, Information Technology, Electrical Engineering, or a related field.
4+ years of experience in network and Linux infrastructure engineering, preferably in a manufacturing or industrial environment.
Deep Linux expertise with Rocky Linux / RHEL, including administration of core infrastructure services: DNS, DHCP, and network storage (NFS).
Hands-on experience with Palo Alto Networks firewalls, including policy management, threat prevention, and configuration of active/standby ISP failover links.
Demonstrated ability to automate infrastructure at scale; proven track record applying Infrastructure as Code (IaC) best practices using Ansible, Terraform, or equivalent tooling.
Strong knowledge of networking fundamentals: TCP/IP, VLANs, routing protocols (OSPF, BGP), switching, and network security.
Experience with enterprise network vendors including Cisco, Arista, and Juniper; familiarity with ruggedized industrial switches (Hirschmann, Cisco IE series, or similar).
Knowledge of cybersecurity best practices aligned with NIST frameworks.
Experience with wireless networking (Wi-Fi 6, cellular/private LTE) in industrial or plant-floor settings.
Experience with network monitoring and observability platforms (Grafana, Zabbix, or similar) and on-call alerting integrations such as PagerDuty.
Ability to review data center and plant-floor physical designs; experience collaborating with cabling vendors and server rack build teams to implement structured cabling best practices.
Comfortable working on the plant floor alongside cross-functional teams including maintenance, engineering, and operations.
Strong troubleshooting, documentation, and communication skills.
Able to participate in on-call rotation and respond to after-hours production-critical incidents.
Experience with Python scripting for network automation, configuration management, and compliance reporting.
Experience with cloud connectivity and hybrid network architectures (AWS, Azure, or GCP) in manufacturing contexts.
Familiarity with MES platforms and their integration with enterprise IT systems.
Knowledge of structured cabling standards (TIA-568, IEC 11801) and data center operations within manufacturing environments.
Experience with SD-WAN solutions for multi-site manufacturing connectivity.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nWe are seeking an experienced Manufacturing Linux / Network Engineer to design, implement, and maintain robust IT and network infrastructure across our manufacturing facilities. The ideal candidate brings deep expertise in Linux systems administration (Red Hat / Rocky Linux), network security (Palo Alto firewalls), storage infrastructure, CI/CD pipelines (Jenkins), and infrastructure automation (Ansible). This role sits at the intersection of enterprise IT and plant-floor operations, and is critical to delivering the high availability, security, and performance that modern manufacturing environments demand.\n\n\nRESPONSIBILITIES\n\n - Design, deploy, and maintain LAN/WAN network infrastructure spanning manufacturing plants, warehouses, cloud providers, and corporate sites.\n\n - Implement and manage high-speed core switching at 10G and 100G using Arista, Juniper, and other enterprise switching platforms; ensure scalable, resilient fabric design.\n\n - Configure, troubleshoot, and optimize Layer 2/3 networking (LACP, VLANs, BGP) and security controls (Palo Alto firewalls, VPNs, NAC, IDS/IPS); manage ISP link failover and path redundancy.\n\n - Deploy, configure, and maintain Linux servers (Red Hat / Rocky Linux) using automation tools including Ansible, MAAS, Foreman, and custom scripting to ensure consistent, repeatable provisioning.\n\n - Monitor network and system performance — uptime, latency, bandwidth utilization, and capacity — across all sites; proactively detect and resolve issues before they impact\n\n - Design and maintain redundancy, failover, QoS, and traffic engineering strategies to support 24/7 manufacturing operations and minimize unplanned downtime.\n\n - Manage structured cabling, Wi-Fi 6/6E wireless infrastructure, and ruggedized networking hardware suited for plant-floor environments.\n\n - Partner with engineering, automation, OT, and IT security teams to ensure secure and reliable connectivity for production and operational systems.\n\n - Lead and contribute to greenfield and brownfield IT/OT modernization projects, including network redesigns for new equipment rollouts and facility expansions.\n\n - Own network documentation including topology diagrams, IP address management (IPAM), and standard operating procedures; keep them current as infrastructure evolves.\n\n - Provide Tier 2/3 support for network and Linux system incidents at manufacturing sites; participate in on-call rotation for production-critical issues.\n\n\nREQUIREMENTS\n\n - Bachelor’s degree in Computer Science, Information Technology, Electrical Engineering, or a related field.\n\n - 4+ years of experience in network and Linux infrastructure engineering, preferably in a manufacturing or industrial environment.\n\n - Deep Linux expertise with Rocky Linux / RHEL, including administration of core infrastructure services: DNS, DHCP, and network storage (NFS).\n\n - Hands-on experience with Palo Alto Networks firewalls, including policy management, threat prevention, and configuration of active/standby ISP failover links.\n\n - Demonstrated ability to automate infrastructure at scale; proven track record applying Infrastructure as Code (IaC) best practices using Ansible, Terraform, or equivalent tooling. \n\n - Strong knowledge of networking fundamentals: TCP/IP, VLANs, routing protocols (OSPF, BGP), switching, and network security.\n\n - Experience with enterprise network vendors including Cisco, Arista, and Juniper; familiarity with ruggedized industrial switches (Hirschmann, Cisco IE series, or similar).\n\n - Knowledge of cybersecurity best practices aligned with NIST frameworks. \n\n - Experience with wireless networking (Wi-Fi 6, cellular/private LTE) in industrial or plant-floor settings. \n\n - Experience with network monitoring and observability platforms (Grafana, Zabbix, or similar) and on-call alerting integrations such as PagerDuty.\n\n - Ability to review data center and plant-floor physical designs; experience collaborating with cabling vendors and server rack build teams to implement structured cabling best practices.\n\n - Comfortable working on the plant floor alongside cross-functional teams including maintenance, engineering, and operations.\n\n - Strong troubleshooting, documentation, and communication skills. \n\n - Able to participate in on-call rotation and respond to after-hours production-critical incidents. \n\n\nPREFERRED QUALIFICATIONS\n\n - Experience with Python scripting for network automation, configuration management, and compliance reporting.\n\n - Experience with cloud connectivity and hybrid network architectures (AWS, Azure, or GCP) in manufacturing contexts.\n\n - Familiarity with MES platforms and their integration with enterprise IT systems. \n\n - Knowledge of structured cabling standards (TIA-568, IEC 11801) and data center operations within manufacturing environments.\n\n - Experience with SD-WAN solutions for multi-site manufacturing connectivity. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"0471b24c-013d-4e9c-a1dd-b11beadb95c7","title":"ML Software Tool Development Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-02-17T15:40:18.389+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/0471b24c-013d-4e9c-a1dd-b11beadb95c7","applyUrl":"https://jobs.ashbyhq.com/cerebras/0471b24c-013d-4e9c-a1dd-b11beadb95c7/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities:
Lead the design and implementation of system-level debugging, validation, and observability platforms.
Develop automated systems for collecting and analyzing numerical, and execution anomalies.
Create visualization and analysis tools to enable efficient root-cause investigation.
Build frameworks for failure classification, regression detection, and anomaly monitoring.
Extend compilers, runtimes, and programming interfaces to support advanced profiling and instrumentation.
Improve system bring-up, low-level debug, and validation workflows.
Partner cross-functionally with compiler, hardware, firmware, runtime, and infrastructure teams.
Establish best practices for debuggability, reliability, and operational excellence.
Lead high-impact initiatives.
Support incident response and drive long-term corrective actions.
Skills & Qualifications
Strong proficiency in C++ and Python, with a track record of building reliable, high-performance systems and tooling.
Demonstrated experience debugging complex hardware/software systems and driving issues to root cause.
Experience analyzing system-level data structures, execution graphs, or dependency networks for diagnostics and validation.
Proven ability to design and build intuitive visualization and analysis tools for complex technical data.
Experience with compiler internals, custom hardware interfaces, or low-level protocol design.
Strong written and verbal communication skills, with the ability to explain technical concepts to diverse stakeholders.
Ability to work independently and lead complex technical projects end-to-end.
Preferred Skills & Qualifications
Familiarity with machine learning training and inference pipelines, especially distributed training and large-model scaling.
Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities:\n\n - Lead the design and implementation of system-level debugging, validation, and observability platforms.\n\n - Develop automated systems for collecting and analyzing numerical, and execution anomalies.\n\n - Create visualization and analysis tools to enable efficient root-cause investigation.\n\n - Build frameworks for failure classification, regression detection, and anomaly monitoring.\n\n - Extend compilers, runtimes, and programming interfaces to support advanced profiling and instrumentation.\n\n - Improve system bring-up, low-level debug, and validation workflows.\n\n - Partner cross-functionally with compiler, hardware, firmware, runtime, and infrastructure teams.\n\n - Establish best practices for debuggability, reliability, and operational excellence.\n\n - Lead high-impact initiatives.\n\n - Support incident response and drive long-term corrective actions.\n\n Skills & Qualifications\n\n - Strong proficiency in C++ and Python, with a track record of building reliable, high-performance systems and tooling.\n\n - Demonstrated experience debugging complex hardware/software systems and driving issues to root cause.\n\n - Experience analyzing system-level data structures, execution graphs, or dependency networks for diagnostics and validation.\n\n - Proven ability to design and build intuitive visualization and analysis tools for complex technical data.\n\n - Experience with compiler internals, custom hardware interfaces, or low-level protocol design.\n\n - Strong written and verbal communication skills, with the ability to explain technical concepts to diverse stakeholders.\n\n - Ability to work independently and lead complex technical projects end-to-end.\n\nPreferred Skills & Qualifications\n\n - Familiarity with machine learning training and inference pipelines, especially distributed training and large-model scaling.\n\n - Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"05bfe83a-64d8-4080-b6e5-81bb9e64b731","title":"Senior Hardware Technical Program Manager","department":"Product Management Departments","team":"Product Management","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-03-23T16:21:47.112+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/05bfe83a-64d8-4080-b6e5-81bb9e64b731","applyUrl":"https://jobs.ashbyhq.com/cerebras/05bfe83a-64d8-4080-b6e5-81bb9e64b731/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Senior Hardware Technical Program Manager at Cerebras, you will spearhead operational excellence for our high-performance AI compute systems and data centers. You will own the end-to-end hardware schedule for design and engineering improvements, report on engineering issues, and define mitigation strategies. You will own the schedule, implementation, and software integration of hardware changes. You will collaborate closely with electrical and system engineering, manufacturing, supply chain, and system software to drive end-to-end schedule of improvements to our wafer-scale engine supercomputers. Your role will be critical in ensuring seamless translation of product strategy and engineering constraints into the creation and execution of massive supercomputer deployments in the US and abroad.
Responsibilities
Own end-to-end program schedule for engineering improvements. Develop and manage comprehensive program plans, including schedules, material plans, and validation plans.
Work with key stakeholders in product management, quality, reliability, supply chain, and executive teams to define program strategy and requirements.
Identify and mitigate technical risks, ensuring program deliverables are met on time and within budget.
Act as the single-threaded owner across product, engineering, supply chain, and software to manage both detailed and high-level product planning.
Develop and implement new processes that improve team efficiency as the business scales.
Collaborate with supply chain, operations, and procurement teams to coordinate component sourcing, vendor management, and logistics.
Identify and implement strategies to manage costs effectively while meeting performance and efficiency targets.
Present program status, metrics, and operational risks to senior leadership
Requirements
Bachelor’s or Master’s degree in computer science, electrical engineering, mechanical engineering, physics, mathematics, a related scientific/engineering discipline, or equivalent practical experience.
8+ years of experience in technical program management, with a focus on hardware, embedded SW, and product planning.
Strong understanding of hardware design processes, product lifecycle management, and manufacturing workflows.
Strong understanding of the intersection of software and hardware, and how hardware changes affect software workflows.
Proven experience effectively managing project priorities across a diverse set of hardware, software, product, and operations disciplines.
Demonstrated ability to work effectively with highly technical cross-functional engineering teams.
Familiarity with project management software, such as MS Project or Smartsheet.
Strong business acumen with experience in cost management and analysis.
Outstanding verbal and written communication skills.
The base salary range for this position is $180,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Senior Hardware Technical Program Manager at Cerebras, you will spearhead operational excellence for our high-performance AI compute systems and data centers. You will own the end-to-end hardware schedule for design and engineering improvements, report on engineering issues, and define mitigation strategies. You will own the schedule, implementation, and software integration of hardware changes. You will collaborate closely with electrical and system engineering, manufacturing, supply chain, and system software to drive end-to-end schedule of improvements to our wafer-scale engine supercomputers. Your role will be critical in ensuring seamless translation of product strategy and engineering constraints into the creation and execution of massive supercomputer deployments in the US and abroad.\n\nResponsibilities \n\n - Own end-to-end program schedule for engineering improvements. Develop and manage comprehensive program plans, including schedules, material plans, and validation plans.\n\n - Work with key stakeholders in product management, quality, reliability, supply chain, and executive teams to define program strategy and requirements.\n\n - Identify and mitigate technical risks, ensuring program deliverables are met on time and within budget.\n\n - Act as the single-threaded owner across product, engineering, supply chain, and software to manage both detailed and high-level product planning.\n\n - Develop and implement new processes that improve team efficiency as the business scales.\n\n - Collaborate with supply chain, operations, and procurement teams to coordinate component sourcing, vendor management, and logistics.\n\n - Identify and implement strategies to manage costs effectively while meeting performance and efficiency targets.\n\n - Present program status, metrics, and operational risks to senior leadership\n\nRequirements\n\n - Bachelor’s or Master’s degree in computer science, electrical engineering, mechanical engineering, physics, mathematics, a related scientific/engineering discipline, or equivalent practical experience. \n\n - 8+ years of experience in technical program management, with a focus on hardware, embedded SW, and product planning.\n\n - Strong understanding of hardware design processes, product lifecycle management, and manufacturing workflows. \n\n - Strong understanding of the intersection of software and hardware, and how hardware changes affect software workflows.\n\n - Proven experience effectively managing project priorities across a diverse set of hardware, software, product, and operations disciplines.\n\n - Demonstrated ability to work effectively with highly technical cross-functional engineering teams.\n\n - Familiarity with project management software, such as MS Project or Smartsheet.\n\n - Strong business acumen with experience in cost management and analysis.\n\n - Outstanding verbal and written communication skills.\n\nThe base salary range for this position is $180,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"07e7ada8-040f-4314-97a4-7b1bc5fee923","title":"Billings and Collections Specialist","department":"Commercial Operations Departments","team":"Finance","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[{"location":"Toronto Office","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-02-13T04:43:42.862+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/07e7ada8-040f-4314-97a4-7b1bc5fee923","applyUrl":"https://jobs.ashbyhq.com/cerebras/07e7ada8-040f-4314-97a4-7b1bc5fee923/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Senior Billing and Collections Analyst, you’ll own the full order-to-invoice cycle, turning delivered hardware, professional services, and compute usage into accurate, timely invoices that support clean financial reporting and on-time customer payment. You’ll serve as a key link between Sales, Services, and Finance by leading month-end billing close activities, translating contract terms into billing in NetSuite, and managing credits and adjustments with audit-ready documentation.
You’ll respond to billing inquiries, resolve order-to-invoice issues before they delay payment, and identify process improvements and automation opportunities. This is a high-impact role where your attention to detail, problem-solving, and cross-functional collaboration strengthen billing accuracy and help build a scalable foundation for growth.
Responsibilities
Own end-to-end billing across hardware, professional services, and compute services, ensuring accurate and timely invoicing.
Perform month-end billing close activities by coordinating inputs from internal teams, validating period activity including compute usage, and resolving exceptions before invoicing.
Execute billing in NetSuite by translating contract terms and operational activity into accurate invoices, billing schedules, and supporting documentation.
Manage billing adjustments including credits, credit memos or notes, voids, and rebills with appropriate approvals, audit-ready support, and clear root-cause tracking.
Support collections by ensuring invoices meet customer requirements including portal submissions, responding to billing inquiries, and resolving issues that delay payment.
Work with Sales, Services, Finance, and Systems teams to resolve order-to-invoice issues and improve upstream data quality.
Maintain SOPs, close checklists, reconciliations, and KPI tracking and reporting, and identify process and automation improvements to strengthen scalability and control.
Skills And Qualifications
Bachelor’s degree in Accounting, Finance, Business, or related field (preferred)
4–7 years of progressive billing or finance operations experience, including ownership of month-end billing close (required)
Hands-on NetSuite experience (required); experience with Advanced Revenue Management (ARM) (preferred)
Advanced Microsoft Excel skills, including large data sets, pivot tables, and complex formulas (required)
Strong attention to detail with proven ability to reconcile billing data, investigate variances, and drive issues to resolution (required)
Strong understanding of billing operations, including invoicing, credits and adjustments, and invoice support documentation (required)
Understanding of internal controls and maintaining audit-ready billing documentation (required)
Experience billing across multiple revenue streams, including hardware, professional services, and usage-based or consumption services (preferred) Strong communication and cross-functional collaboration skills; ability to operate independently in a lean environment (required)
Experience improving billing processes through documentation, standardization, and automation (preferred)
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Senior Billing and Collections Analyst, you’ll own the full order-to-invoice cycle, turning delivered hardware, professional services, and compute usage into accurate, timely invoices that support clean financial reporting and on-time customer payment. You’ll serve as a key link between Sales, Services, and Finance by leading month-end billing close activities, translating contract terms into billing in NetSuite, and managing credits and adjustments with audit-ready documentation.\n\nYou’ll respond to billing inquiries, resolve order-to-invoice issues before they delay payment, and identify process improvements and automation opportunities. This is a high-impact role where your attention to detail, problem-solving, and cross-functional collaboration strengthen billing accuracy and help build a scalable foundation for growth.\n\nResponsibilities\n\n - Own end-to-end billing across hardware, professional services, and compute services, ensuring accurate and timely invoicing.\n\n - Perform month-end billing close activities by coordinating inputs from internal teams, validating period activity including compute usage, and resolving exceptions before invoicing.\n\n - Execute billing in NetSuite by translating contract terms and operational activity into accurate invoices, billing schedules, and supporting documentation.\n\n - Manage billing adjustments including credits, credit memos or notes, voids, and rebills with appropriate approvals, audit-ready support, and clear root-cause tracking.\n\n - Support collections by ensuring invoices meet customer requirements including portal submissions, responding to billing inquiries, and resolving issues that delay payment.\n\n - Work with Sales, Services, Finance, and Systems teams to resolve order-to-invoice issues and improve upstream data quality.\n\n - Maintain SOPs, close checklists, reconciliations, and KPI tracking and reporting, and identify process and automation improvements to strengthen scalability and control.\n\nSkills And Qualifications \n\n - Bachelor’s degree in Accounting, Finance, Business, or related field (preferred)\n\n - 4–7 years of progressive billing or finance operations experience, including ownership of month-end billing close (required)\n\n - Hands-on NetSuite experience (required); experience with Advanced Revenue Management (ARM) (preferred)\n\n - Advanced Microsoft Excel skills, including large data sets, pivot tables, and complex formulas (required)\n\n - Strong attention to detail with proven ability to reconcile billing data, investigate variances, and drive issues to resolution (required)\n\n - Strong understanding of billing operations, including invoicing, credits and adjustments, and invoice support documentation (required)\n\n - Understanding of internal controls and maintaining audit-ready billing documentation (required)\n\n - Experience billing across multiple revenue streams, including hardware, professional services, and usage-based or consumption services (preferred) Strong communication and cross-functional collaboration skills; ability to operate independently in a lean environment (required)\n\n - Experience improving billing processes through documentation, standardization, and automation (preferred)\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"088ab192-e04a-4819-8152-0d0f8c015299","title":"Principal Engineer, AI Inference Reliability","department":"Software","team":"Cloud","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2025-10-29T02:39:37.801+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/088ab192-e04a-4819-8152-0d0f8c015299","applyUrl":"https://jobs.ashbyhq.com/cerebras/088ab192-e04a-4819-8152-0d0f8c015299/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the role
We’re looking for a hands-on Reliability Tech Lead (IC) to own the mission of making Cerebras Inference the most reliable AI service in the world. You will drive reliability strategy and execution across our inference stack, from client SDKs and public-cloud multi-region deployments to wafer-scale systems in specialized data centers.
In this role, you will define SLOs and incident-response frameworks, design and implement reliability mechanisms at scale, and partner across hundreds of engineers to ensure our service meets world-class reliability standards.
If you are passionate about building and operating massive-scale, low-latency, high-reliability distributed systems, we want to hear from you.
Responsibilities:
Define and drive reliability strategy: establish SLOs and ensure alignment across engineering.
Design and implement reliability mechanisms: build and evolve systems for fault detection, graceful degradation, failover, throttling, and recovery across multiple regions and data centers.
Lead large-scale incident management: own postmortems, root-cause analysis, and prevention loops for reliability-related incidents.
Architect for reliability and observability: influence system design for redundancy, durability, and debuggability.
Develop reliability tooling: create internal tools and frameworks for chaos testing, load simulation, and distributed fault injection.
Collaborate broadly: work across software, infrastructure, and hardware teams to ensure reliability is embedded into every layer of our inference service.
Monitor and communicate reliability metrics: build dashboards and alerts that measure service health and provide actionable insights.
Mentor and influence: guide engineers and set best practices for designing, testing, and operating reliable large-scale systems.
Skills & Qualifications:
Bachelor's or master's degree in computer science or related field.
7+ years of experience in backend, infrastructure, or reliability engineering for large-scale distributed systems.
Strong programming skills in at least one popular backend programming language such as Python, C++, Go, or Rust.
Deep and hard-earned experience of reliability principles: SLO/SLI/SLA design, incident response, and postmortem culture.
Excellent communication and cross-functional leadership skills.
Bonus: prior experience building large-scale AI infrastructure systems.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the role \n\nWe’re looking for a hands-on Reliability Tech Lead (IC) to own the mission of making Cerebras Inference the most reliable AI service in the world. You will drive reliability strategy and execution across our inference stack, from client SDKs and public-cloud multi-region deployments to wafer-scale systems in specialized data centers. \n\nIn this role, you will define SLOs and incident-response frameworks, design and implement reliability mechanisms at scale, and partner across hundreds of engineers to ensure our service meets world-class reliability standards. \n\nIf you are passionate about building and operating massive-scale, low-latency, high-reliability distributed systems, we want to hear from you. \n\nResponsibilities: \n\n - Define and drive reliability strategy: establish SLOs and ensure alignment across engineering. \n\n - Design and implement reliability mechanisms: build and evolve systems for fault detection, graceful degradation, failover, throttling, and recovery across multiple regions and data centers. \n\n - Lead large-scale incident management: own postmortems, root-cause analysis, and prevention loops for reliability-related incidents. \n\n - Architect for reliability and observability: influence system design for redundancy, durability, and debuggability. \n\n - Develop reliability tooling: create internal tools and frameworks for chaos testing, load simulation, and distributed fault injection. \n\n - Collaborate broadly: work across software, infrastructure, and hardware teams to ensure reliability is embedded into every layer of our inference service. \n\n - Monitor and communicate reliability metrics: build dashboards and alerts that measure service health and provide actionable insights. \n\n - Mentor and influence: guide engineers and set best practices for designing, testing, and operating reliable large-scale systems. \n\nSkills & Qualifications: \n\n - Bachelor's or master's degree in computer science or related field. \n\n - 7+ years of experience in backend, infrastructure, or reliability engineering for large-scale distributed systems. \n\n - Strong programming skills in at least one popular backend programming language such as Python, C++, Go, or Rust. \n\n - Deep and hard-earned experience of reliability principles: SLO/SLI/SLA design, incident response, and postmortem culture. \n\n - Excellent communication and cross-functional leadership skills. \n\n - Bonus: prior experience building large-scale AI infrastructure systems. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"0fbdfff1-78cc-4fac-b99a-a90b5f244cc2","title":"Distributed Systems Cluster Security Software – Engineering Lead","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2025-03-24T19:36:56.049+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/0fbdfff1-78cc-4fac-b99a-a90b5f244cc2","applyUrl":"https://jobs.ashbyhq.com/cerebras/0fbdfff1-78cc-4fac-b99a-a90b5f244cc2/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
In this role, you will be the security czar for the Cerebras’s AI cluster product. Such AI clusters have 100’s of Wafer-scale accelerator systems, 1000’s of high-end servers, and several 1000’s of networking ports including switches. Plus, there will be network attached storage, all in a large-scale datacenter.
You will ensure that Cerebras’s large-scale AI clusters are secured through first-principles, best practices, security-first based engineering. Cerebras cluster involves complex HW components, networking and a vertically integrated cluster management software stack – all the way from a bare-metal deployment that brings up an operational cluster to a suite of cluster management software that enables multi-tenant higher-level training and inference services to be hosted on such large clusters.
Your role will be to ensure both end-to-end security as well as privacy of such cluster use-cases. You will develop security engineering solutions that have the necessary network access control, user access controls, and world-class multi-tenancy solution
Responsibilities
Be the primary engineering face and owner of cluster security.
Provide strong technical leadership in cluster security for the company.
Actively work with corporate security, and customers to identify and define security enhancements needed.
Build engineering driven software that will provide guardrails, detection solution and response tools for vulnerabilities at all layers of vertical stack (includes HW and SW).
Straddle vertically and horizontally cross functional collaboration to ensure end-to-end cluster software is secure.
Develop, maintain and execute roadmap of the cluster security product.
Build an outstanding engineering team to deliver world-class security solution.
Skills & Qualifications
3+ years of demonstrated engineering leadership/management role in distributed systems security.
Proven track record of delivering product, launching and deploying secured distributed solutions to customers.
Excellent communication, articulation, collaboration and ability to act as a stakeholder.
Tough decision-making skills with data and trade-off analysis.
Outstanding sense for product and user journeys, out-of-box thinker.
Outstanding road map and schedule execution skills under tight timeline and budgets.
Strong background in multi-tenancy of large scale clusters is necessary.
Strong technical experience in computer and cluster networks is necessary.
Strong technical background in distributed systems software development (K8s and its ecosystem) is preferred.
Technical experience with bare metal cluster management software and related monitoring is preferred.
The salary range for this position is $140,000 - $240,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nIn this role, you will be the security czar for the Cerebras’s AI cluster product. Such AI clusters have 100’s of Wafer-scale accelerator systems, 1000’s of high-end servers, and several 1000’s of networking ports including switches. Plus, there will be network attached storage, all in a large-scale datacenter.\n\nYou will ensure that Cerebras’s large-scale AI clusters are secured through first-principles, best practices, security-first based engineering. Cerebras cluster involves complex HW components, networking and a vertically integrated cluster management software stack – all the way from a bare-metal deployment that brings up an operational cluster to a suite of cluster management software that enables multi-tenant higher-level training and inference services to be hosted on such large clusters.\n\nYour role will be to ensure both end-to-end security as well as privacy of such cluster use-cases. You will develop security engineering solutions that have the necessary network access control, user access controls, and world-class multi-tenancy solution\n\nResponsibilities\n\n - Be the primary engineering face and owner of cluster security.\n\n - Provide strong technical leadership in cluster security for the company.\n\n - Actively work with corporate security, and customers to identify and define security enhancements needed.\n\n - Build engineering driven software that will provide guardrails, detection solution and response tools for vulnerabilities at all layers of vertical stack (includes HW and SW).\n\n - Straddle vertically and horizontally cross functional collaboration to ensure end-to-end cluster software is secure.\n\n - Develop, maintain and execute roadmap of the cluster security product.\n\n - Build an outstanding engineering team to deliver world-class security solution.\n\nSkills & Qualifications\n\n - 3+ years of demonstrated engineering leadership/management role in distributed systems security.\n\n - Proven track record of delivering product, launching and deploying secured distributed solutions to customers.\n\n - Excellent communication, articulation, collaboration and ability to act as a stakeholder.\n\n - Tough decision-making skills with data and trade-off analysis.\n\n - Outstanding sense for product and user journeys, out-of-box thinker.\n\n - Outstanding road map and schedule execution skills under tight timeline and budgets.\n\n - Strong background in multi-tenancy of large scale clusters is necessary.\n\n - Strong technical experience in computer and cluster networks is necessary.\n\n - Strong technical background in distributed systems software development (K8s and its ecosystem) is preferred.\n\n - Technical experience with bare metal cluster management software and related monitoring is preferred.\n\nThe salary range for this position is $140,000 - $240,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"13eec2f8-b308-40b4-8194-f3c133ccb3bc","title":"Engineering Manager, Kernel Reliability ","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-01-08T18:01:49.310+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/13eec2f8-b308-40b4-8194-f3c133ccb3bc","applyUrl":"https://jobs.ashbyhq.com/cerebras/13eec2f8-b308-40b4-8194-f3c133ccb3bc/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We're looking for a deeply technical, hands-on engineering leader for our on-field Kernel Reliability team. You will lead a high performing team to tackle a critical challenge: improving the reliability of our advanced compute clusters and the underlying inference, training, and internal production services. In this role, you'll set the technical vision while staying close to the code and designing solutions that will scale to our exponentially growing system production and software service offerings. If you have proven expertise in software or hardware reliability, diagnostic tool building, or failure analysis and debugging, we want to hear from you.
Responsibilities
Provide hands-on technical leadership, owning the technical vision and roadmap for the kernel-centric reliability of our internal and customer-facing systems
Assist System and Cluster Operations teams on reducing system and service downtime after failure by providing tooling and manual intervention for failure analysis and diagnostic
Work with the Debug Team to enhance debug tools with the goal of speeding up failure analysis
Collaborate with SW teams to improve the software stack, including Kernels, to improve on-field debugging and failure analysis
Work with the ASIC an HW architecture teams to codesign the next generation architectures with reliability and ease of debug in mind
Lead, mentor, and grow a high-caliber team of engineers, fostering a culture of technical excellence and rapid execution.
Skills & Qualifications
6+ years in software engineering, with 3+ years leading teams in SW/HW reliability, debug, diagnostic, failure analysis or related fields
Expertise in parallel and distributed programming (message passing, multicore, GPU, embeded, etc.), debug and diagnostic tool development or expert usage (debuggers, core dump handling, code sanitizers, etc.), experience debugging distributed and parallel applications (deadlocks, livelocks, race conditions, etc.), deep understanding of computer architectures (instruction pipelining, multithreading, networking, etc.)
Operations & Monitoring: Strong background in monitoring and reliability engineering (incident response, post-mortem analysis, etc.)
Leadership & Collaboration: Demonstrated ability to recruit and retain high-performing teams, mentor engineers, and partner cross-functionally to deliver customer-facing products.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\n \n\nWe're looking for a deeply technical, hands-on engineering leader for our on-field Kernel Reliability team. You will lead a high performing team to tackle a critical challenge: improving the reliability of our advanced compute clusters and the underlying inference, training, and internal production services. In this role, you'll set the technical vision while staying close to the code and designing solutions that will scale to our exponentially growing system production and software service offerings. If you have proven expertise in software or hardware reliability, diagnostic tool building, or failure analysis and debugging, we want to hear from you.\n\n \n\nResponsibilities\n\n - Provide hands-on technical leadership, owning the technical vision and roadmap for the kernel-centric reliability of our internal and customer-facing systems\n\n - Assist System and Cluster Operations teams on reducing system and service downtime after failure by providing tooling and manual intervention for failure analysis and diagnostic\n\n - Work with the Debug Team to enhance debug tools with the goal of speeding up failure analysis\n\n - Collaborate with SW teams to improve the software stack, including Kernels, to improve on-field debugging and failure analysis\n\n - Work with the ASIC an HW architecture teams to codesign the next generation architectures with reliability and ease of debug in mind\n\n - Lead, mentor, and grow a high-caliber team of engineers, fostering a culture of technical excellence and rapid execution. \n\nSkills & Qualifications\n\n - 6+ years in software engineering, with 3+ years leading teams in SW/HW reliability, debug, diagnostic, failure analysis or related fields \n\n - Expertise in parallel and distributed programming (message passing, multicore, GPU, embeded, etc.), debug and diagnostic tool development or expert usage (debuggers, core dump handling, code sanitizers, etc.), experience debugging distributed and parallel applications (deadlocks, livelocks, race conditions, etc.), deep understanding of computer architectures (instruction pipelining, multithreading, networking, etc.)\n\n - Operations & Monitoring: Strong background in monitoring and reliability engineering (incident response, post-mortem analysis, etc.)\n\n - Leadership & Collaboration: Demonstrated ability to recruit and retain high-performing teams, mentor engineers, and partner cross-functionally to deliver customer-facing products.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1bf0ea92-b0fd-4163-b44c-3564e67b15c1","title":"Principal SRE - AI Inference","department":"Software","team":"Cloud","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-07-06T20:38:40.281+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/1bf0ea92-b0fd-4163-b44c-3564e67b15c1","applyUrl":"https://jobs.ashbyhq.com/cerebras/1bf0ea92-b0fd-4163-b44c-3564e67b15c1/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for leading model builders such as OpenAI and other frontier labs.
As a Principal SRE, you will define and drive the technical architecture for scaling our inference fleet through self-service delivery, shared observability, capacity orchestration, rollout safety, and operational automation. This role starts with 2–3 weeks of hands-on operational immersion to build deep context on the current stack, production pain points, and high-stakes workflows.
From there, your mandate shifts to architecting the “tomorrow” layer: a unified capacity management and production control plane that enables reliable capacity planning, workload placement, rollout safety, validation, and operational decision-making across large-scale inference infrastructure.
Success in the first year means core engineering teams, product managers, external customers, and cluster stakeholders can execute critical operational workflows through self-service systems with strong guardrails, clear ownership, and minimal dependency on expert SRE operators.
You will collaborate with the tech leads and the leadership team across core, cluster, cloud, and product stakeholders. This work will shift reliability from an ops-only burden to a shared engineering discipline that underpins frontier AI inference at scale.
If you are a proven Principal engineer who enjoys turning complexity into elegant reliability at scale, this is your chance to lead this transformation from the front.
This role does not require 24/7 on-call rotations.
Key Responsibilities
Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions.
Architect self-service platforms and internal tooling that let product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs.
Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets; blameless postmortems; chaos testing; and capacity forecasting across multi-datacenter and on-prem environments.
Mentor senior SREs, support critical incident escalations, and use production pain points to prioritize the highest-leverage automation work.
Measure and drive impact through clear metrics, including toil reduction, deployment velocity, SLO compliance, MTTR, and adoption of self-service workflows.
Required Experience & Skills
15+ years in SRE, infrastructure engineering, or platform engineering, with a record of setting technical direction and delivering reliability improvements at large scale in FAANG, hyperscaler, frontier AI, or similarly demanding production environments.
Deep experience with large-scale compute fleets, internal control planes, schedulers, orchestration systems, capacity management, and reliability automation.
Experience defining and driving cross-team architecture for production control planes, capacity orchestration, fleet management, or self-service infrastructure platforms with clear operational ownership.
Strong judgment in converging fragmented workflows, tools, and teams into coherent architectures that improve reliability, efficiency, and operational leverage.
Ability to lead complex, ambiguous technical programs end to end; influence senior cross-functional stakeholders; mentor senior engineers; and communicate technical strategy clearly.
Hands-on experience with production observability, incident response, and SLO-based reliability management across metrics, logs, traces, alerting, dashboards, and operational review loops.
Nice-to-Haves
Experience with Bazel or other large-scale build systems in production.
Background in AI/ML inference systems, including model serving runtimes, disaggregated inference, GPU orchestration, latency and accuracy SLOs, or drift monitoring.
Prior work on predictive autoscaling, chaos engineering, or cost-aware capacity management for compute-intensive workloads.
Location
SF Bay Area
Toronto
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for leading model builders such as OpenAI and other frontier labs.\n\nAs a Principal SRE, you will define and drive the technical architecture for scaling our inference fleet through self-service delivery, shared observability, capacity orchestration, rollout safety, and operational automation. This role starts with 2–3 weeks of hands-on operational immersion to build deep context on the current stack, production pain points, and high-stakes workflows.\n\nFrom there, your mandate shifts to architecting the “tomorrow” layer: a unified capacity management and production control plane that enables reliable capacity planning, workload placement, rollout safety, validation, and operational decision-making across large-scale inference infrastructure.\n\nSuccess in the first year means core engineering teams, product managers, external customers, and cluster stakeholders can execute critical operational workflows through self-service systems with strong guardrails, clear ownership, and minimal dependency on expert SRE operators.\n\nYou will collaborate with the tech leads and the leadership team across core, cluster, cloud, and product stakeholders. This work will shift reliability from an ops-only burden to a shared engineering discipline that underpins frontier AI inference at scale.\n\nIf you are a proven Principal engineer who enjoys turning complexity into elegant reliability at scale, this is your chance to lead this transformation from the front.\n\nThis role does not require 24/7 on-call rotations.\n\nKey Responsibilities\n\n - Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions.\n\n - Architect self-service platforms and internal tooling that let product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs.\n\n - Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets; blameless postmortems; chaos testing; and capacity forecasting across multi-datacenter and on-prem environments.\n\n - Mentor senior SREs, support critical incident escalations, and use production pain points to prioritize the highest-leverage automation work.\n\n - Measure and drive impact through clear metrics, including toil reduction, deployment velocity, SLO compliance, MTTR, and adoption of self-service workflows.\n\nRequired Experience & Skills\n\n - 15+ years in SRE, infrastructure engineering, or platform engineering, with a record of setting technical direction and delivering reliability improvements at large scale in FAANG, hyperscaler, frontier AI, or similarly demanding production environments.\n\n - Deep experience with large-scale compute fleets, internal control planes, schedulers, orchestration systems, capacity management, and reliability automation.\n\n - Experience defining and driving cross-team architecture for production control planes, capacity orchestration, fleet management, or self-service infrastructure platforms with clear operational ownership.\n\n - Strong judgment in converging fragmented workflows, tools, and teams into coherent architectures that improve reliability, efficiency, and operational leverage.\n\n - Ability to lead complex, ambiguous technical programs end to end; influence senior cross-functional stakeholders; mentor senior engineers; and communicate technical strategy clearly.\n\n - Hands-on experience with production observability, incident response, and SLO-based reliability management across metrics, logs, traces, alerting, dashboards, and operational review loops.\n\nNice-to-Haves\n\n - Experience with Bazel or other large-scale build systems in production.\n\n - Background in AI/ML inference systems, including model serving runtimes, disaggregated inference, GPU orchestration, latency and accuracy SLOs, or drift monitoring.\n\n - Prior work on predictive autoscaling, chaos engineering, or cost-aware capacity management for compute-intensive workloads.\n\nLocation\n\n - SF Bay Area\n\n - Toronto\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1c63f451-b4d1-44e4-a31a-8c0cd3045222","title":"Manager kernel software ","department":"Software","team":"Software","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2025-10-06T15:45:47.388+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/1c63f451-b4d1-44e4-a31a-8c0cd3045222","applyUrl":"https://jobs.ashbyhq.com/cerebras/1c63f451-b4d1-44e4-a31a-8c0cd3045222/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.
You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.
Responsibilities
Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.
Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.
Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.
Using mathematical models and analysis to measure the software performance and inform design decisions.
Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.
Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.
Skills & Qualifications
Bachelor’s, Master’s, PhD, or foreign equivalent in Computer Science, Computer Engineering, Mathematics, or a related field.
Proven experience leading technical teams, including mentoring engineers, setting technical direction, and driving execution.
Strong understanding of hardware architecture concepts and willingness to dive into new system architectures.
Proficiency in C++ and Python; experience with low-level systems programming.
Familiarity with library/API development best practices and performance optimization.
Excellent debugging skills across complex, layered software stacks.
Preferred Skills & Qualifications
Experience leading teams in kernel development, performance optimization, or low-level systems programming.
Strong background in parallel algorithms and distributed memory systems.
Hands-on experience with accelerators such as GPUs, FPGAs, or other custom hardware.
Familiarity with machine learning workloads and frameworks like TensorFlow and PyTorch.
Understanding of HPC kernels and strategies for optimizing them on modern architectures.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.\n\nYou will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.\n\nResponsibilities \n\n \n\n - Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.\n\n - Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.\n\n - Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.\n\n - Using mathematical models and analysis to measure the software performance and inform design decisions.\n\n - Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.\n\n - Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.\n\n - Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.\n\n \n\nSkills & Qualifications \n\n - Bachelor’s, Master’s, PhD, or foreign equivalent in Computer Science, Computer Engineering, Mathematics, or a related field. \n\n - Proven experience leading technical teams, including mentoring engineers, setting technical direction, and driving execution. \n\n - Strong understanding of hardware architecture concepts and willingness to dive into new system architectures. \n\n - Proficiency in C++ and Python; experience with low-level systems programming. \n\n - Familiarity with library/API development best practices and performance optimization. \n\n - Excellent debugging skills across complex, layered software stacks. \n\nPreferred Skills & Qualifications \n\n - Experience leading teams in kernel development, performance optimization, or low-level systems programming. \n\n - Strong background in parallel algorithms and distributed memory systems. \n\n - Hands-on experience with accelerators such as GPUs, FPGAs, or other custom hardware. \n\n - Familiarity with machine learning workloads and frameworks like TensorFlow and PyTorch. \n\n - Understanding of HPC kernels and strategies for optimizing them on modern architectures.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1c8cdbc4-bd74-46df-9645-bb910eaa7a37","title":"Staff Inference ML Runtime Engineer","department":"Software","team":"Cloud","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2025-11-25T18:10:40.280+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/1c8cdbc4-bd74-46df-9645-bb910eaa7a37","applyUrl":"https://jobs.ashbyhq.com/cerebras/1c8cdbc4-bd74-46df-9645-bb910eaa7a37/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
The Inference ML Engineering team at Cerebras Systems is dedicated to enabling our fast generative inference solution through simple APIs powered by a distributed runtime that runs on large clusters of our own hardware. Our mission is to empower enterprises, developers, and researchers to unlock the full potential of our platform, leveraging its performance, scalability, and flexibility.
As a Senior Software Engineer on the Inference ML Engineering team, you will design and implement APIs, machine learning features, and tools that enable state-of-the-art generative AI models to run efficiently on our custom hardware. You will collaborate with cross-functional teams to build scalable, high-performance inference solutions while helping shape the evolution of our ML ecosystem.
Responsibilities
Drive and provide technical guidance to a team of software engineers working on complex machine learning integration projects.
Design and implement ML features (e.g., structured outputs, biased sampling, predicted outputs) that improve performance of generative AI models at inference time.
Design and implement high-throughput, low-latency multimodal inference models that support delivery of image, audio, and video inputs and outputs.
Maintain our scalable serving backend for handling many concurrent requests per minute.
Scale our inference service by implementing detailed observability throughout the entire stack.
Analyze and improve latency, throughput, memory usage, and compute efficiency on the service and the implementation of various features.
Optimize software to accelerate generative LLM inference by achieving high throughput and low latency.
Stay up-to-date with advancements in machine learning and deep learning, and apply state-of-the-art techniques to enhance our solutions.
Evaluate trade-offs between different approaches, clearly articulate design choices, and develop detailed proposals for implementing new features.
Uncover, scope, and prioritize significant areas of technical debt across the software stack to ensure continued high quality of the inference service.
Build and maintain robust automated test suites to ensure software quality, performance, and reliability.
Contribute to an agile team environment by delivering high-quality software and adhering to agile development practices.
Lead cross-functional initiatives across the company to deliver high-quality inference solutions.
Skills & Qualifications
Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Mathematics, or a related field.
8+ years of experience in large-scale software engineering, with a focus on deep learning or related domains.
Proficiency in Python for building and maintaining scalable systems.
Advanced proficiency in C++, with an emphasis on multi-threaded programming, performance optimization, and system-level development.
Demonstrated experience driving cross-functional projects.
Experience building and scaling large-scale inference systems for LLMs or multimodal models.
Familiarity with LLM serving frameworks, such as vLLM, SGLang, and TensorRT-LLM.
Solid understanding of software architectural patterns for large-scale, high-performance applications.
Hands-on experience with ML frameworks, such as PyTorch, and a strong understanding of their underlying architectures.
Strong problem-solving skills, with the ability to balance technical depth with practical implementation constraints.
Exceptional communication and presentation skills, with the ability to work both independently and collaboratively across multidisciplinary teams.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nThe Inference ML Engineering team at Cerebras Systems is dedicated to enabling our fast generative inference solution through simple APIs powered by a distributed runtime that runs on large clusters of our own hardware. Our mission is to empower enterprises, developers, and researchers to unlock the full potential of our platform, leveraging its performance, scalability, and flexibility.\n\nAs a Senior Software Engineer on the Inference ML Engineering team, you will design and implement APIs, machine learning features, and tools that enable state-of-the-art generative AI models to run efficiently on our custom hardware. You will collaborate with cross-functional teams to build scalable, high-performance inference solutions while helping shape the evolution of our ML ecosystem.\n\nResponsibilities\n\n - Drive and provide technical guidance to a team of software engineers working on complex machine learning integration projects.\n\n - Design and implement ML features (e.g., structured outputs, biased sampling, predicted outputs) that improve performance of generative AI models at inference time.\n\n - Design and implement high-throughput, low-latency multimodal inference models that support delivery of image, audio, and video inputs and outputs.\n\n - Maintain our scalable serving backend for handling many concurrent requests per minute.\n\n - Scale our inference service by implementing detailed observability throughout the entire stack.\n\n - Analyze and improve latency, throughput, memory usage, and compute efficiency on the service and the implementation of various features.\n\n - Optimize software to accelerate generative LLM inference by achieving high throughput and low latency.\n\n - Stay up-to-date with advancements in machine learning and deep learning, and apply state-of-the-art techniques to enhance our solutions.\n\n - Evaluate trade-offs between different approaches, clearly articulate design choices, and develop detailed proposals for implementing new features.\n\n - Uncover, scope, and prioritize significant areas of technical debt across the software stack to ensure continued high quality of the inference service.\n\n - Build and maintain robust automated test suites to ensure software quality, performance, and reliability.\n\n - Contribute to an agile team environment by delivering high-quality software and adhering to agile development practices.\n\n - Lead cross-functional initiatives across the company to deliver high-quality inference solutions.\n\nSkills & Qualifications\n\n - Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Mathematics, or a related field.\n\n - 8+ years of experience in large-scale software engineering, with a focus on deep learning or related domains.\n\n - Proficiency in Python for building and maintaining scalable systems.\n\n - Advanced proficiency in C++, with an emphasis on multi-threaded programming, performance optimization, and system-level development.\n\n - Demonstrated experience driving cross-functional projects.\n\n - Experience building and scaling large-scale inference systems for LLMs or multimodal models.\n\n - Familiarity with LLM serving frameworks, such as vLLM, SGLang, and TensorRT-LLM.\n\n - Solid understanding of software architectural patterns for large-scale, high-performance applications.\n\n - Hands-on experience with ML frameworks, such as PyTorch, and a strong understanding of their underlying architectures.\n\n - Strong problem-solving skills, with the ability to balance technical depth with practical implementation constraints.\n\n - Exceptional communication and presentation skills, with the ability to work both independently and collaboratively across multidisciplinary teams.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1e1e6848-b35e-465e-96b3-3cd5538cc1f1","title":"Director / Senior Director, Critical Facility Operations ","department":"Hardware Departments","team":"Datacenters","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-06-03T01:43:45.239+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/1e1e6848-b35e-465e-96b3-3cd5538cc1f1","applyUrl":"https://jobs.ashbyhq.com/cerebras/1e1e6848-b35e-465e-96b3-3cd5538cc1f1/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
At Cerebras, we build systems that redefine the scale of compute. That ambition extends beyond silicon into the infrastructure that powers it.
We are looking for a Director / Sr. Director of Critical Facility Operations to lead the environments that enable next-generation AI workloads. This leader will own availability, operational integrity, and performance across a colocation-driven data center footprint—ensuring our infrastructure operates with precision, predictability, and zero room for error.
This is not a traditional facilities role. You will operate at the intersection of mission-critical engineering, vendor orchestration, and operational excellence, building systems and teams that can scale with the most demanding compute environments in the world.
Responsibilities
Drive a no-downtime operating model across all facilities
Own uptime performance end-to-end including incident response and RCA
Build a culture where failures are analyzed and not repeated
Vendor & Colocation
Architect and run a high-discipline vendor operating model
Convert vendor relationships into measurable systems
Lead deep operational reviews and enforce accountability
Contracts
Align SLAs, incentives, and performance
Eliminate ambiguity in ownership and response
Safety
Build a zero-incident safety culture
Ensure rigor in high-risk procedures
Maintenance
Transform preventive maintenance into failure prevention
Implement predictive strategies where possible
Operations
Standardize SOPs, MOPs, and EOPs
Build a high-signal operating rhythm
Benchmark against hyperscale operators
Leadership
Build high-performing, high-agency teams
Drive ownership, speed, and technical excellence
Scaling
Ensure operational readiness for new builds
Influence design and site strategy
Skills & Qualifications
12–15+ years in mission-critical facilities or data center operations
Experience managing multi-site, vendor-heavy environments
Strong expertise in electrical and mechanical systems
Proven track record in improving uptime and performance
Success Metrics
Availability and SLA performance
Incident reduction and MTTR improvement
Vendor performance and accountability
Safety metrics
Maintenance quality and execution
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAt Cerebras, we build systems that redefine the scale of compute. That ambition extends beyond silicon into the infrastructure that powers it.\n\nWe are looking for a Director / Sr. Director of Critical Facility Operations to lead the environments that enable next-generation AI workloads. This leader will own availability, operational integrity, and performance across a colocation-driven data center footprint—ensuring our infrastructure operates with precision, predictability, and zero room for error.\n\nThis is not a traditional facilities role. You will operate at the intersection of mission-critical engineering, vendor orchestration, and operational excellence, building systems and teams that can scale with the most demanding compute environments in the world.\n\nResponsibilities\n\n - Drive a no-downtime operating model across all facilities\n\n - Own uptime performance end-to-end including incident response and RCA\n\n - Build a culture where failures are analyzed and not repeated\n\nVendor & Colocation\n\n - Architect and run a high-discipline vendor operating model\n\n - Convert vendor relationships into measurable systems\n\n - Lead deep operational reviews and enforce accountability\n\nContracts\n\n - Align SLAs, incentives, and performance\n\n - Eliminate ambiguity in ownership and response\n\nSafety\n\n - Build a zero-incident safety culture\n\n - Ensure rigor in high-risk procedures\n\nMaintenance\n\n - Transform preventive maintenance into failure prevention\n\n - Implement predictive strategies where possible\n\nOperations\n\n - Standardize SOPs, MOPs, and EOPs\n\n - Build a high-signal operating rhythm\n\n - Benchmark against hyperscale operators\n\nLeadership\n\n - Build high-performing, high-agency teams\n\n - Drive ownership, speed, and technical excellence\n\nScaling\n\n - Ensure operational readiness for new builds\n\n - Influence design and site strategy\n\nSkills & Qualifications\n\n - 12–15+ years in mission-critical facilities or data center operations\n\n - Experience managing multi-site, vendor-heavy environments\n\n - Strong expertise in electrical and mechanical systems\n\n - Proven track record in improving uptime and performance\n\nSuccess Metrics\n\n - Availability and SLA performance\n\n - Incident reduction and MTTR improvement\n\n - Vendor performance and accountability\n\n - Safety metrics\n\n - Maintenance quality and execution\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1f47a4ca-bd55-4fd6-bdc0-4916ad35e872","title":"Sr. Program Manager, DC Portfolio & Vendor Mgt.","department":"Hardware Departments","team":"Datacenters","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[{"location":"Remote Office","address":null}],"publishedAt":"2026-07-13T15:55:57.167+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/1f47a4ca-bd55-4fd6-bdc0-4916ad35e872","applyUrl":"https://jobs.ashbyhq.com/cerebras/1f47a4ca-bd55-4fd6-bdc0-4916ad35e872/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Role
The Datacenter Portfolio & Vendor Management Lead will own the operational backbone of Cerebras' global datacenter program.
This person partners closely with Engineering, Infrastructure, Finance, Legal, Procurement, Accounting, and Executive Leadership to manage strategic supplier relationships, commercial agreements, budgets, payment operations, and portfolio reporting.
This is a highly cross-functional role requiring exceptional organizational skills, commercial judgment, and the ability to drive execution across multiple simultaneous infrastructure programs.
Responsibilities
Portfolio Management
Own the centralized portfolio of global datacenter projects
Track capacity deployments, schedules, milestones, risks, and dependencies
Develop executive dashboards and portfolio health reporting
Coordinate planning across Engineering, Operations, Finance, and Supply Chain
Contract Management
Own lifecycle management of datacenter contracts
Coordinate contract negotiations with Legal and Procurement
Track key commercial terms, renewals, amendments, and obligations
Maintain repository of supplier agreements and commercial documentation
Vendor Management
Manage strategic relationships with:
Colocation providers
Construction partners
Power and utility providers
Network providers
Equipment vendors
Professional services partners
Track vendor performance against SLAs and KPIs
Drive quarterly business reviews
Resolve commercial escalations
Financial Operations
Track purchase commitments and contract values
Partner with Finance on forecasting and budget management
Coordinate invoice approvals and payment workflows
Monitor spend against approved budgets
Support capital expenditure planning
Program Operations
Build scalable operational processes for the rapidly growing datacenter organization
Drive governance reviews
Maintain risk registers
Coordinate executive reporting
Improve portfolio management tooling and reporting automation
Qualifications
Required
8+ years managing complex infrastructure, construction, or technology programs
Experience managing large vendor portfolios
Strong contract administration experience
Budget ownership experience ($10M+ preferred)
Experience working with Finance and Legal organizations
Excellent project management skills
Ability to work across highly technical engineering organizations
Outstanding communication and executive presentation skills
Preferred
Experience with one or more:
Hyperscale datacenters
Cloud infrastructure
AI infrastructure
Colocation providers
Construction management
Critical facilities
Supply chain operations
ERP systems (Oracle, SAP, NetSuite)
Coupa
Jira
Smartsheet
Airtable
Tableau or Power BI
Success in this Role
Within your first year you will:
Build operational rigor across Cerebras' global datacenter portfolio
Improve visibility into project health and financial performance
Establish scalable vendor governance processes
Streamline contract and payment workflows
Enable infrastructure teams to execute faster by reducing operational overhead
Establish metrics of economic KPI’s in all leases in the portfolio (Contracted vs actual)
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nThe Role\n\nThe Datacenter Portfolio & Vendor Management Lead will own the operational backbone of Cerebras' global datacenter program.\n\nThis person partners closely with Engineering, Infrastructure, Finance, Legal, Procurement, Accounting, and Executive Leadership to manage strategic supplier relationships, commercial agreements, budgets, payment operations, and portfolio reporting.\n\nThis is a highly cross-functional role requiring exceptional organizational skills, commercial judgment, and the ability to drive execution across multiple simultaneous infrastructure programs.\n\nResponsibilities\n\nPortfolio Management\n\n - Own the centralized portfolio of global datacenter projects\n\n - Track capacity deployments, schedules, milestones, risks, and dependencies\n\n - Develop executive dashboards and portfolio health reporting\n\n - Coordinate planning across Engineering, Operations, Finance, and Supply Chain\n\nContract Management\n\n - Own lifecycle management of datacenter contracts\n\n - Coordinate contract negotiations with Legal and Procurement\n\n - Track key commercial terms, renewals, amendments, and obligations\n\n - Maintain repository of supplier agreements and commercial documentation\n\nVendor Management\n\n - Manage strategic relationships with:\n \n - Colocation providers\n \n - Construction partners\n \n - Power and utility providers\n \n - Network providers\n \n - Equipment vendors\n \n - Professional services partners\n\n - Track vendor performance against SLAs and KPIs\n\n - Drive quarterly business reviews\n\n - Resolve commercial escalations\n\nFinancial Operations\n\n - Track purchase commitments and contract values\n\n - Partner with Finance on forecasting and budget management\n\n - Coordinate invoice approvals and payment workflows\n\n - Monitor spend against approved budgets\n\n - Support capital expenditure planning\n\nProgram Operations\n\n - Build scalable operational processes for the rapidly growing datacenter organization\n\n - Drive governance reviews\n\n - Maintain risk registers\n\n - Coordinate executive reporting\n\n - Improve portfolio management tooling and reporting automation\n\nQualifications\n\nRequired\n\n - 8+ years managing complex infrastructure, construction, or technology programs\n\n - Experience managing large vendor portfolios\n\n - Strong contract administration experience\n\n - Budget ownership experience ($10M+ preferred)\n\n - Experience working with Finance and Legal organizations\n\n - Excellent project management skills\n\n - Ability to work across highly technical engineering organizations\n\n - Outstanding communication and executive presentation skills\n\nPreferred\n\nExperience with one or more:\n\n - Hyperscale datacenters\n\n - Cloud infrastructure\n\n - AI infrastructure\n\n - Colocation providers\n\n - Construction management\n\n - Critical facilities\n\n - Supply chain operations\n\n - ERP systems (Oracle, SAP, NetSuite)\n\n - Coupa\n\n - Jira\n\n - Smartsheet\n\n - Airtable\n\n - Tableau or Power BI\n\nSuccess in this Role\n\nWithin your first year you will:\n\n - Build operational rigor across Cerebras' global datacenter portfolio\n\n - Improve visibility into project health and financial performance\n\n - Establish scalable vendor governance processes\n\n - Streamline contract and payment workflows\n\n - Enable infrastructure teams to execute faster by reducing operational overhead\n\n - Establish metrics of economic KPI’s in all leases in the portfolio (Contracted vs actual)\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"1fd0045d-8469-4dc6-ab13-d4fd0bf26f8b","title":"Kernel Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-02-23T15:19:15.020+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/1fd0045d-8469-4dc6-ab13-d4fd0bf26f8b","applyUrl":"https://jobs.ashbyhq.com/cerebras/1fd0045d-8469-4dc6-ab13-d4fd0bf26f8b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.
You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.
Responsibilities
Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.
Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.
Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.
Using mathematical models and analysis to measure the software performance and inform design decisions.
Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.
Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.
Skills And Qualifications
Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.
Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.
Skilled in C++ and Python programming languages.
Good knowledge of library and/or API development best practices.
Strong debugging skills and knowledge of debugging complex software stack.
Preferred Skills And Qualifications
Experience in kernel development and/or testing.
Familiarity with parallel algorithms and distributed memory systems.
Experience in programming accelerators such as GPUs and FPGAs.
Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch.
Familiarity with HPC kernels and their optimization.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.\n\nYou will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.\n\nResponsibilities\n\n - Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.\n\n - Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.\n\n - Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.\n\n - Using mathematical models and analysis to measure the software performance and inform design decisions.\n\n - Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.\n\n - Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.\n\n - Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.\n\nSkills And Qualifications\n\n - Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.\n\n - Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.\n\n - Skilled in C++ and Python programming languages.\n\n - Good knowledge of library and/or API development best practices.\n\n - Strong debugging skills and knowledge of debugging complex software stack.\n\nPreferred Skills And Qualifications\n\n - Experience in kernel development and/or testing.\n\n - Familiarity with parallel algorithms and distributed memory systems.\n\n - Experience in programming accelerators such as GPUs and FPGAs.\n\n - Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch.\n\n - Familiarity with HPC kernels and their optimization.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"20010f8f-5ede-469a-b432-c38dc223e11c","title":"Manufacturing Automation Engineer","department":"Manufacturing Departments","team":"Manufacturing","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-06-30T22:07:02.864+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/20010f8f-5ede-469a-b432-c38dc223e11c","applyUrl":"https://jobs.ashbyhq.com/cerebras/20010f8f-5ede-469a-b432-c38dc223e11c/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Job Summary
We are seeking a skilled and motivated Manufacturing Automation Engineer to design, implement, maintain, and optimize automated manufacturing assembly and test systems. The ideal candidate will collaborate with cross-functional teams to improve production efficiency, enhance product quality, reduce downtime, and support continuous improvement initiatives through advanced automation technologies.
Key Responsibilities
Design, develop, and implement automation solutions for manufacturing processes.
Program, troubleshoot, and optimize PLCs, HMIs, SCADA systems, robotics, and industrial control systems.
Support the installation, commissioning, and validation of new production equipment.
Analyze manufacturing processes and identify opportunities to improve productivity, quality, safety, and cost.
Perform root cause analysis of equipment failures and implement corrective actions.
Develop and maintain electrical schematics, control system documentation, and standard operating procedures.
Collaborate with production, maintenance, quality, and engineering teams to resolve technical issues.
Lead or support capital automation projects from concept through implementation.
Ensure compliance with safety regulations, industry standards, and company policies.
Monitor equipment performance using data analysis and recommend continuous improvement initiatives.
Train production and maintenance personnel on new automation systems and equipment.
Maintain spare parts inventories and support preventive and predictive maintenance programs.
Required Qualifications
Bachelor's degree in Electrical Engineering, Mechanical Engineering, Mechatronics Engineering, Automation Engineering, or a related technical field.
3+ years of experience in manufacturing automation, industrial controls, or process engineering.
Experience programming PLCs (Allen-Bradley, Siemens, Mitsubishi, Omron, or similar).
Knowledge of industrial communication protocols such as Ethernet/IP, Modbus, Profinet, or DeviceNet.
Experience with robotics integration and automated material handling systems.
Strong understanding of electrical controls, sensors, actuators, servo systems, and VFDs.
Ability to read and interpret electrical schematics, P&IDs, and mechanical drawings.
Strong troubleshooting, analytical, and problem-solving skills.
Excellent communication and project management abilities.
Preferred Qualifications
Experience with Industry 4.0 technologies, IIoT, and data analytics.
Knowledge of vision inspection systems and machine safety standards.
Experience with SQL databases, Python, C#, or other programming languages.
Familiarity with Lean Manufacturing, Six Sigma, and continuous improvement methodologies.
Professional certifications in automation or controls engineering are a plus.
Key Competencies
Technical problem-solving
Project management
Process optimization
Continuous improvement mindset
Cross-functional collaboration
Attention to detail
Time management
Safety-first approach
Working Conditions
Manufacturing plant environment with exposure to industrial machinery.
Travel to contract manufacturing sites and suppliers
May require off-shift or weekend support during equipment installations or production emergencies.
Performance Metrics
Success in this role will be measured by:
Improvement in overall equipment effectiveness (OEE)
Increased production efficiency
Successful implementation of automation projects
Reduction in manufacturing defects
Compliance with safety and quality standards
Achievement of project timelines and budgets
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nJob Summary\n\nWe are seeking a skilled and motivated Manufacturing Automation Engineer to design, implement, maintain, and optimize automated manufacturing assembly and test systems. The ideal candidate will collaborate with cross-functional teams to improve production efficiency, enhance product quality, reduce downtime, and support continuous improvement initiatives through advanced automation technologies.\n\nKey Responsibilities\n\n - Design, develop, and implement automation solutions for manufacturing processes.\n\n - Program, troubleshoot, and optimize PLCs, HMIs, SCADA systems, robotics, and industrial control systems.\n\n - Support the installation, commissioning, and validation of new production equipment.\n\n - Analyze manufacturing processes and identify opportunities to improve productivity, quality, safety, and cost.\n\n - Perform root cause analysis of equipment failures and implement corrective actions.\n\n - Develop and maintain electrical schematics, control system documentation, and standard operating procedures.\n\n - Collaborate with production, maintenance, quality, and engineering teams to resolve technical issues.\n\n - Lead or support capital automation projects from concept through implementation.\n\n - Ensure compliance with safety regulations, industry standards, and company policies.\n\n - Monitor equipment performance using data analysis and recommend continuous improvement initiatives.\n\n - Train production and maintenance personnel on new automation systems and equipment.\n\n - Maintain spare parts inventories and support preventive and predictive maintenance programs.\n\nRequired Qualifications\n\n - Bachelor's degree in Electrical Engineering, Mechanical Engineering, Mechatronics Engineering, Automation Engineering, or a related technical field.\n\n - 3+ years of experience in manufacturing automation, industrial controls, or process engineering.\n\n - Experience programming PLCs (Allen-Bradley, Siemens, Mitsubishi, Omron, or similar).\n\n - Knowledge of industrial communication protocols such as Ethernet/IP, Modbus, Profinet, or DeviceNet.\n\n - Experience with robotics integration and automated material handling systems.\n\n - Strong understanding of electrical controls, sensors, actuators, servo systems, and VFDs.\n\n - Ability to read and interpret electrical schematics, P&IDs, and mechanical drawings.\n\n - Strong troubleshooting, analytical, and problem-solving skills.\n\n - Excellent communication and project management abilities.\n\nPreferred Qualifications\n\n - Experience with Industry 4.0 technologies, IIoT, and data analytics.\n\n - Knowledge of vision inspection systems and machine safety standards.\n\n - Experience with SQL databases, Python, C#, or other programming languages.\n\n - Familiarity with Lean Manufacturing, Six Sigma, and continuous improvement methodologies.\n\n - Professional certifications in automation or controls engineering are a plus.\n\nKey Competencies\n\n - Technical problem-solving\n\n - Project management\n\n - Process optimization\n\n - Continuous improvement mindset\n\n - Cross-functional collaboration\n\n - Attention to detail\n\n - Time management\n\n - Safety-first approach\n\nWorking Conditions\n\n - Manufacturing plant environment with exposure to industrial machinery.\n\n - Travel to contract manufacturing sites and suppliers\n\n - May require off-shift or weekend support during equipment installations or production emergencies.\n\nPerformance Metrics\n\nSuccess in this role will be measured by:\n\n - Improvement in overall equipment effectiveness (OEE)\n\n - Increased production efficiency\n\n - Successful implementation of automation projects\n\n - Reduction in manufacturing defects\n\n - Compliance with safety and quality standards\n\n - Achievement of project timelines and budgets\n\n\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"20dab4de-51f4-4704-8b72-5896b83ac37b","title":"Sr. Member of Technical Staff","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-05-08T19:37:52.248+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/20dab4de-51f4-4704-8b72-5896b83ac37b","applyUrl":"https://jobs.ashbyhq.com/cerebras/20dab4de-51f4-4704-8b72-5896b83ac37b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are seeking a Sr. Member of Technical Staff to design and develop software features that support system resiliency and high availability across distributed environments. In this role, you will help build and maintain scalable AI inference services, develop cloud-based deployment workflows, improve system reliability through automation, and collaborate across engineering teams to deliver high-performance software solutions.
Responsibilities
Design and develop software features that support system resiliency and high availability, including automated recovery mechanisms and fault-tolerant architecture across distributed environments.
Develop and maintain cloud-based deployment workflows for AI inference software using AWS tools and services to support low-latency and scalable system performance.
Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks.
Use parallel programming techniques (e.g., multi-threading, asynchronous processing) to maximize resource efficiency on AWS compute instances.
Develop software components to support visualization and analysis of system performance metrics, enhancing the monitoring and usability of inference services.
Develop inference software in Docker containers and define Kubernetes orchestration strategies that ensure software reliability and efficient scaling.
Develop automated scripts to detect and mitigate common failure modes, improving software system reliability.
Debug issues related to model deployment, container orchestration, and networking configurations, documenting steps to reproduce and root-cause defects.
Triage and resolve defects in the software service by analyzing logs, metrics, and distributed traces using tools like AWS CloudWatch, Grafana, or custom Python scripts.
Work with Product Management and User Experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging.
Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers.
Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability.
Skills & Qualifications
Minimum Requirements
Master's degree or foreign equivalent degree in Computer Science, or a related field.
18 months of experience as an Information Security Analyst, Software Engineer, Sr. Member of Technical Staff, IT Senior Applications Engineer, or a related occupation.
Required Skills
Infrastructure-as-Code and deployment automation: Terraform, AWS CloudFormation, AWS CDK, and Ansible.
Containerization and orchestration: Docker, Kubernetes, AWS EKS, AWS Elastic Container Service (ECS), AWS Fargate, and Helm.
Compute and serverless services: AWS EC2, AWS Lambda functions, and Auto Scaling Groups.
Monitoring, logging, and distributed tracing: AWS CloudWatch, AWS X-Ray, ELK (Elasticsearch, Logstash, Kibana), Prometheus, and Grafana.
Programming languages and frameworks: Python, Node.js, JavaScript, and Flask.
Data storage and caching: PostgreSQL, Redis, and NFS.
CI/CD and version control: Jenkins and Git.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are seeking a Sr. Member of Technical Staff to design and develop software features that support system resiliency and high availability across distributed environments. In this role, you will help build and maintain scalable AI inference services, develop cloud-based deployment workflows, improve system reliability through automation, and collaborate across engineering teams to deliver high-performance software solutions.\n\nResponsibilities\n\n - Design and develop software features that support system resiliency and high availability, including automated recovery mechanisms and fault-tolerant architecture across distributed environments.\n\n - Develop and maintain cloud-based deployment workflows for AI inference software using AWS tools and services to support low-latency and scalable system performance.\n\n - Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks.\n\n - Use parallel programming techniques (e.g., multi-threading, asynchronous processing) to maximize resource efficiency on AWS compute instances.\n\n - Develop software components to support visualization and analysis of system performance metrics, enhancing the monitoring and usability of inference services.\n\n - Develop inference software in Docker containers and define Kubernetes orchestration strategies that ensure software reliability and efficient scaling.\n\n - Develop automated scripts to detect and mitigate common failure modes, improving software system reliability.\n\n - Debug issues related to model deployment, container orchestration, and networking configurations, documenting steps to reproduce and root-cause defects.\n\n - Triage and resolve defects in the software service by analyzing logs, metrics, and distributed traces using tools like AWS CloudWatch, Grafana, or custom Python scripts.\n\n - Work with Product Management and User Experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging.\n\n - Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers.\n\n - Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability.\n\nSkills & Qualifications\n\nMinimum Requirements\n\n - Master's degree or foreign equivalent degree in Computer Science, or a related field.\n\n - 18 months of experience as an Information Security Analyst, Software Engineer, Sr. Member of Technical Staff, IT Senior Applications Engineer, or a related occupation.\n\n - Required Skills\n\n - Infrastructure-as-Code and deployment automation: Terraform, AWS CloudFormation, AWS CDK, and Ansible.\n\n - Containerization and orchestration: Docker, Kubernetes, AWS EKS, AWS Elastic Container Service (ECS), AWS Fargate, and Helm.\n\n - Compute and serverless services: AWS EC2, AWS Lambda functions, and Auto Scaling Groups.\n\n - Monitoring, logging, and distributed tracing: AWS CloudWatch, AWS X-Ray, ELK (Elasticsearch, Logstash, Kibana), Prometheus, and Grafana.\n\n - Programming languages and frameworks: Python, Node.js, JavaScript, and Flask.\n\n - Data storage and caching: PostgreSQL, Redis, and NFS.\n\n - CI/CD and version control: Jenkins and Git.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"224566db-c2c9-4b81-9534-a9917ea1aaa6","title":"Software Engineer in Test - ML API Features","department":"Software","team":"Software","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-07-02T15:50:58.787+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/224566db-c2c9-4b81-9534-a9917ea1aaa6","applyUrl":"https://jobs.ashbyhq.com/cerebras/224566db-c2c9-4b81-9534-a9917ea1aaa6/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As a Software Engineer in Test for the ML API features team, you will be involved in testing AI/ML models for accuracy, fairness, and performance. You will play a pivotal role in bringing together and delivering all software and hardware components for Cerebras API Features. You will focus on SW components feature integration and quality and Pre-deployment/production validation for Cerebras inference solution. As part of this role, you will influence the best testing practice, good debugging methodology, effective cross team communication and advocate for world-class products.
Understand new features end-to-end, and develop tests and tools to ensure quality.
Contribute to industry standard benchmarks.
Drive automation to improve internal efficiency.
Understand trade off between coverage and resource requirements.
Work in a highly agile environment where priorities change frequently.
Effectively communicate across teams and timezones.
2+ years of relevant industry experience in Software integration, development or quality.
Strong automation and programming skills using one or more programming languages like Python, C++ or go.
Experience in testing compute/machine learning/networking/storage systems within a large-scale enterprise environment.
Experience in debugging issues across distributed scale out deployment.
Experience working effectively across teams, including product development, product management, customer operations, and field teams.
Excellent verbal and written communication skills.
Strong organizational skills, teamwork, and can-do attitude.
Experience working with geographically dispersed teams across time zones.
Experience in working with ML workloads such as LLM/Multimodal training or inference.
Experience with hardware architecture, performance optimizations, compilers and ML frameworks.
Experience working with distributed systems, cloud and security.
Experience working with microservices deployment, debugging and orchestration.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nAs a Software Engineer in Test for the ML API features team, you will be involved in testing AI/ML models for accuracy, fairness, and performance. You will play a pivotal role in bringing together and delivering all software and hardware components for Cerebras API Features. You will focus on SW components feature integration and quality and Pre-deployment/production validation for Cerebras inference solution. As part of this role, you will influence the best testing practice, good debugging methodology, effective cross team communication and advocate for world-class products.\n\n\n\nRESPONSIBILITIES\n\n - Understand new features end-to-end, and develop tests and tools to ensure quality.\n\n - Contribute to industry standard benchmarks.\n\n - Drive automation to improve internal efficiency.\n\n - Understand trade off between coverage and resource requirements.\n\n - Work in a highly agile environment where priorities change frequently.\n\n - Effectively communicate across teams and timezones.\n\n\nSKILLS & QUALIFICATIONS\n\n - 2+ years of relevant industry experience in Software integration, development or quality.\n\n - Strong automation and programming skills using one or more programming languages like Python, C++ or go.\n\n - Experience in testing compute/machine learning/networking/storage systems within a large-scale enterprise environment.\n\n - Experience in debugging issues across distributed scale out deployment.\n\n - Experience working effectively across teams, including product development, product management, customer operations, and field teams.\n\n - Excellent verbal and written communication skills.\n\n - Strong organizational skills, teamwork, and can-do attitude.\n\n - Experience working with geographically dispersed teams across time zones.\n\n\nPREFERRED SKILLS & QUALIFICATIONS\n\n - Experience in working with ML workloads such as LLM/Multimodal training or inference.\n\n - Experience with hardware architecture, performance optimizations, compilers and ML frameworks.\n\n - Experience working with distributed systems, cloud and security.\n\n - Experience working with microservices deployment, debugging and orchestration.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"2484eb99-2bbf-45df-a3c5-bdd337584726","title":"Principal Engineer, Inference Cloud ","department":"Software","team":"Cloud","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2025-09-29T12:43:55.551+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/2484eb99-2bbf-45df-a3c5-bdd337584726","applyUrl":"https://jobs.ashbyhq.com/cerebras/2484eb99-2bbf-45df-a3c5-bdd337584726/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We're hiring a Principal Engineer for our Inference Cloud Platform. This team owns the cloud layer behind our Inference Service, including availability, latency, reliability, and multi-region scale.
This is one of the most senior IC roles on the team, for someone who can identify the highest-leverage platform problems, set direction across multiple teams, define long-term architecture, and write production code on critical paths.
Many of the key decisions are ambiguous at the outset; you’ll need to frame the problem, make tradeoffs, and drive execution without a clear spec.
The scope includes multi-region traffic architecture, graceful degradation under bursty AI workloads, high-QPS performance, and the operating model for a platform that needs to remain fast and available under changing demand. You'll partner closely with ML, Product and Infrastructure teams.
Responsibilities
Problem Definition & Prioritization. Identify the most important technical problems for the platform, often before there's a clear ask. Make explicit tradeoff decisions about what the platform will and won't support, with reasoning that holds up under scrutiny from senior engineering leadership.
Platform Direction. Set the long-term technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, service boundaries, and system evolution over time.
Reliability & Performance. Architect active-active systems with rapid failover and graceful degradation (circuit breaking, backpressure, load shedding) with clear SLOs. Drive improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.
Code & Design Reviews. Contribute production code in critical paths, review designs and implementations, and make architectural decisions including build-vs-buy tradeoffs with long-term operational consequences.
Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.
Technical Strategy Beyond Your Team. Drive platform-wide decisions across adjacent teams on reliability, API design, capacity planning, and deployment strategy through strong technical judgment. Translate product and business requirements into scalable system designs and drive alignment on shared infrastructure decisions.
Mentorship. Raise the quality of technical decision-making across teams through design feedback, pairing, and clear engineering standards.
Skills & Qualifications
10+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.
Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services.
Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale, demonstrated through systems you built directly.
Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.
Strong proficiency in backend or systems languages such as Go, C++, or Python, with the expectation that you can contribute production code directly.
Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLI/SLO/SLA-driven operations.
Ability to influence senior engineers, technical leads, and cross-functional partners through technical credibility, communication, and judgment.
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads is a plus.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nWe're hiring a Principal Engineer for our Inference Cloud Platform. This team owns the cloud layer behind our Inference Service, including availability, latency, reliability, and multi-region scale. \n\nThis is one of the most senior IC roles on the team, for someone who can identify the highest-leverage platform problems, set direction across multiple teams, define long-term architecture, and write production code on critical paths. \n\nMany of the key decisions are ambiguous at the outset; you’ll need to frame the problem, make tradeoffs, and drive execution without a clear spec. \n\nThe scope includes multi-region traffic architecture, graceful degradation under bursty AI workloads, high-QPS performance, and the operating model for a platform that needs to remain fast and available under changing demand. You'll partner closely with ML, Product and Infrastructure teams. \n\nResponsibilities \n\n - Problem Definition & Prioritization. Identify the most important technical problems for the platform, often before there's a clear ask. Make explicit tradeoff decisions about what the platform will and won't support, with reasoning that holds up under scrutiny from senior engineering leadership. \n\n - Platform Direction. Set the long-term technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, service boundaries, and system evolution over time. \n\n - Reliability & Performance. Architect active-active systems with rapid failover and graceful degradation (circuit breaking, backpressure, load shedding) with clear SLOs. Drive improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand. \n\n - Code & Design Reviews. Contribute production code in critical paths, review designs and implementations, and make architectural decisions including build-vs-buy tradeoffs with long-term operational consequences. \n\n - Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor. \n\n - Technical Strategy Beyond Your Team. Drive platform-wide decisions across adjacent teams on reliability, API design, capacity planning, and deployment strategy through strong technical judgment. Translate product and business requirements into scalable system designs and drive alignment on shared infrastructure decisions. \n\n - Mentorship. Raise the quality of technical decision-making across teams through design feedback, pairing, and clear engineering standards. \n\nSkills & Qualifications \n\n - 10+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure. \n\n - Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services. \n\n - Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale, demonstrated through systems you built directly. \n\n - Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus. \n\n - Strong proficiency in backend or systems languages such as Go, C++, or Python, with the expectation that you can contribute production code directly. \n\n - Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLI/SLO/SLA-driven operations. \n\n - Ability to influence senior engineers, technical leads, and cross-functional partners through technical credibility, communication, and judgment. \n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads is a plus. \n\n \n\n \n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"24e42002-7f6d-4769-9ce0-0d844757cc0e","title":"Member of Technical Staff (Software Engineer) ","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-05-08T19:43:17.308+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/24e42002-7f6d-4769-9ce0-0d844757cc0e","applyUrl":"https://jobs.ashbyhq.com/cerebras/24e42002-7f6d-4769-9ce0-0d844757cc0e/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking a Software Engineer to develop and maintain high-performance, low-latency inference infrastructure. This role focuses on deploying and optimizing scalable inference services, collaborating with cross-functional teams, and ensuring reliable, production-ready machine learning infrastructure.
Responsibilities
Implement infrastructure to support high-performance, low-latency inference service.
Deploy and configure Kubernetes services to ensure scalability and reliability of inference workloads.
Optimize resource allocation and auto-scaling policies to handle variable inference demand while minimizing operational costs.
Integrate inference services with containerized environments using Docker and Kubernetes for orchestration.
Ensure high availability and fault tolerance by implementing multi-region deployments and disaster recovery strategies.
Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks.
Collaborate with machine learning engineers to validate inference accuracy and performance against functional and latency requirements.
Triage and resolve defects in the service by analyzing logs, metrics, and distributed traces.
Debug issues related to model deployment, container orchestration, or networking configurations, documenting steps to reproduce and root-cause defects.
Collaborate with cross-functional teams to address performance regressions, scalability issues, or integration failures in the inference pipeline.
Develop automated scripts to detect and mitigate common failure modes, improving system reliability.
Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers.
Work with product management and user experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging.
Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability.
Participate in release planning and prioritization discussions to align infrastructure development with customer needs and business objectives.
Skills & Qualifications
Master's degree (or foreign equivalent) in Computer Science or a related field.
One (1) year of experience as a Software Developer, Student/Intern (Software Developer), Member of Technical Staff (Software Engineer), Software Engineer, or a related occupation.
Employer accepts full-time or equivalent part-time experience gained before, during, or after graduate studies.
Required Skills:
Docker and Kubernetes;
Java or C++;
ActiveMQ and Kafka;
Python or Groovy;
JavaScript or TypeScript;
Linux;
SQL, OracleDB, and Redis; and
Git
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\nWe are seeking a Software Engineer to develop and maintain high-performance, low-latency inference infrastructure. This role focuses on deploying and optimizing scalable inference services, collaborating with cross-functional teams, and ensuring reliable, production-ready machine learning infrastructure.\nResponsibilities\n\n - Implement infrastructure to support high-performance, low-latency inference service.\n\n - Deploy and configure Kubernetes services to ensure scalability and reliability of inference workloads.\n\n - Optimize resource allocation and auto-scaling policies to handle variable inference demand while minimizing operational costs.\n\n - Integrate inference services with containerized environments using Docker and Kubernetes for orchestration.\n\n - Ensure high availability and fault tolerance by implementing multi-region deployments and disaster recovery strategies.\n\n - Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks.\n\n - Collaborate with machine learning engineers to validate inference accuracy and performance against functional and latency requirements.\n\n - Triage and resolve defects in the service by analyzing logs, metrics, and distributed traces.\n\n - Debug issues related to model deployment, container orchestration, or networking configurations, documenting steps to reproduce and root-cause defects.\n\n - Collaborate with cross-functional teams to address performance regressions, scalability issues, or integration failures in the inference pipeline.\n\n - Develop automated scripts to detect and mitigate common failure modes, improving system reliability.\n\n - Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers.\n\n - Work with product management and user experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging.\n\n - Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability.\n\n - Participate in release planning and prioritization discussions to align infrastructure development with customer needs and business objectives.\n\nSkills & Qualifications\n\n\nMINIMUM REQUIREMENTS\n\n - Master's degree (or foreign equivalent) in Computer Science or a related field.\n\n - One (1) year of experience as a Software Developer, Student/Intern (Software Developer), Member of Technical Staff (Software Engineer), Software Engineer, or a related occupation.\n\n - Employer accepts full-time or equivalent part-time experience gained before, during, or after graduate studies.\n\nRequired Skills:\n\n - Docker and Kubernetes;\n\n - Java or C++;\n\n - ActiveMQ and Kafka;\n\n - Python or Groovy;\n\n - JavaScript or TypeScript;\n\n - Linux;\n\n - SQL, OracleDB, and Redis; and\n\n - Git\n\n\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"270407eb-1452-4a36-8f8c-7d64263eaa0a","title":"Staff Kernel Optimzation Engineer ","department":"Software","team":"Software","employmentType":"FullTime","location":"Remote Office","secondaryLocations":[],"publishedAt":"2026-02-05T16:04:08.521+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/270407eb-1452-4a36-8f8c-7d64263eaa0a","applyUrl":"https://jobs.ashbyhq.com/cerebras/270407eb-1452-4a36-8f8c-7d64263eaa0a/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.
You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.
Responsibilities
Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.
Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.
Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.
Using mathematical models and analysis to measure the software performance and inform design decisions.
Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.
Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.
Skills And Qualifications
Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.
Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.
Skilled in C++ and Python programming languages.
Good knowledge of library and/or API development best practices.
Strong debugging skills and knowledge of debugging complex software stack.
Preferred Skills And Qualifications
Experience in kernel development and/or testing.
Familiarity with parallel algorithms and distributed memory systems.
Experience in programming accelerators such as GPUs and FPGAs.
Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch.
Familiarity with HPC kernels and their optimization.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n \n\nAbout The Role\nAs a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.\nYou will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.\nResponsibilities\n\n - Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.\n\n - Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.\n\n - Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.\n\n - Using mathematical models and analysis to measure the software performance and inform design decisions.\n\n - Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.\n\n - Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.\n\n - Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.\n\nSkills And Qualifications\n\n - Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.\n\n - Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.\n\n - Skilled in C++ and Python programming languages.\n\n - Good knowledge of library and/or API development best practices.\n\n - Strong debugging skills and knowledge of debugging complex software stack.\n\nPreferred Skills And Qualifications\n\n - Experience in kernel development and/or testing.\n\n - Familiarity with parallel algorithms and distributed memory systems.\n\n - Experience in programming accelerators such as GPUs and FPGAs.\n\n - Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch.\n\n - Familiarity with HPC kernels and their optimization.\n\n \n \n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"2a133db0-a8bf-4945-8320-e5aff8d333cc","title":"IT SRE Team Lead","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-04-09T00:41:09.734+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/2a133db0-a8bf-4945-8320-e5aff8d333cc","applyUrl":"https://jobs.ashbyhq.com/cerebras/2a133db0-a8bf-4945-8320-e5aff8d333cc/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking an experienced IT SRE Team Lead to build and run the reliability function for Cerebras' internal technology estate.
The IT SRE Team Lead will be responsible for the availability, performance, and operational quality of the systems Cerebras employees rely on every day, including identity, endpoint management, collaboration, SaaS, and internal networking. The right candidate will bring a software engineering mindset to IT operations, treating corporate infrastructure as code, with measurable SLOs, automated remediation, and a ruthless focus on eliminating toil.
You will build and lead a small, high-leverage team of engineers who build tooling, write automation, and respond when things break. You will partner closely with the security, networking, and infrastructure teams to make sure the internal environment stays fast, stable, and secure as the company scales.
Responsibilities
Define and own the reliability strategy for internal IT systems, including SLOs, error budgets, and operational health reporting.
Build and lead a team of IT SRE engineers focused on automation, observability, and incident response for corporate systems.
Design and implement automation to eliminate manual IT work across provisioning, access management, patching, and lifecycle operations.
Instrument internal services and SaaS integrations with monitoring, alerting, and on-call workflows.
Run incident response for IT outages, including root cause analysis and durable remediation.
Drive infrastructure-as-code and GitOps practices across IT-owned systems.
Partner with security and networking teams on identity, access, and network reliability.
Skills And Qualifications
Minimum 8 years of experience in SRE, DevOps, or IT engineering roles, with at least 2 years in a leadership capacity.
Direct hands on experience with AI coding tools, building and deploying AI agents for triage and bug fixes.
Strong software engineering background with hands-on experience in Python, Go, or similar, and comfort writing production-grade automation.
Deep experience with identity platforms (Okta, Entra), endpoint management (Jamf, Intune), and SaaS integration patterns.
Hands-on experience with infrastructure-as-code tools (Terraform) and CI/CD pipelines applied to IT systems.
Proven track record of running on-call rotations, defining SLOs, and driving operational maturity in a fast-moving environment.
Experience supporting highly technical engineering populations where uptime and speed both matter.
Strong organizational skills with the ability to multitask and prioritize.
Detail-oriented with the ability to anticipate the needs of customers and internal stakeholders.
Proactive, adaptable, and able to thrive in a rapidly changing environment.
Excellent verbal and written communication skills.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nWe are seeking an experienced IT SRE Team Lead to build and run the reliability function for Cerebras' internal technology estate. \n\nThe IT SRE Team Lead will be responsible for the availability, performance, and operational quality of the systems Cerebras employees rely on every day, including identity, endpoint management, collaboration, SaaS, and internal networking. The right candidate will bring a software engineering mindset to IT operations, treating corporate infrastructure as code, with measurable SLOs, automated remediation, and a ruthless focus on eliminating toil. \n\nYou will build and lead a small, high-leverage team of engineers who build tooling, write automation, and respond when things break. You will partner closely with the security, networking, and infrastructure teams to make sure the internal environment stays fast, stable, and secure as the company scales. \n\nResponsibilities \n\n - Define and own the reliability strategy for internal IT systems, including SLOs, error budgets, and operational health reporting. \n\n - Build and lead a team of IT SRE engineers focused on automation, observability, and incident response for corporate systems. \n\n - Design and implement automation to eliminate manual IT work across provisioning, access management, patching, and lifecycle operations. \n\n - Instrument internal services and SaaS integrations with monitoring, alerting, and on-call workflows. \n\n - Run incident response for IT outages, including root cause analysis and durable remediation. \n\n - Drive infrastructure-as-code and GitOps practices across IT-owned systems. \n\n - Partner with security and networking teams on identity, access, and network reliability. \n\nSkills And Qualifications \n\n - Minimum 8 years of experience in SRE, DevOps, or IT engineering roles, with at least 2 years in a leadership capacity. \n\n - Direct hands on experience with AI coding tools, building and deploying AI agents for triage and bug fixes. \n\n - Strong software engineering background with hands-on experience in Python, Go, or similar, and comfort writing production-grade automation. \n\n - Deep experience with identity platforms (Okta, Entra), endpoint management (Jamf, Intune), and SaaS integration patterns. \n\n - Hands-on experience with infrastructure-as-code tools (Terraform) and CI/CD pipelines applied to IT systems. \n\n - Proven track record of running on-call rotations, defining SLOs, and driving operational maturity in a fast-moving environment. \n\n - Experience supporting highly technical engineering populations where uptime and speed both matter. \n\n - Strong organizational skills with the ability to multitask and prioritize. \n\n - Detail-oriented with the ability to anticipate the needs of customers and internal stakeholders. \n\n - Proactive, adaptable, and able to thrive in a rapidly changing environment. \n\n - Excellent verbal and written communication skills. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"2b22599f-b1ee-46ef-8684-1475bc49bac0","title":"Cloud Infrastructure Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[{"location":"Toronto Office","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-07-13T13:23:54.197+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/2b22599f-b1ee-46ef-8684-1475bc49bac0","applyUrl":"https://jobs.ashbyhq.com/cerebras/2b22599f-b1ee-46ef-8684-1475bc49bac0/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities:
Design, build, and operate secure, scalable cloud infrastructure and identity platforms in AWS and our own data centers.
Implement and manage IAM, IGA, authentication, authorization, SSO, MFA, identity lifecycle management, and provisioning/deprovisioning solutions using modern identity platforms and standards such as SAML, OAuth2, OIDC, and SCIM.
Develop automation, integrations, and infrastructure-as-code solutions using Terraform and programming languages such as Python and Go.
Design and implement security controls for AI-powered systems, including controlled, audited, and governed agent workflows, while contributing to core security services such as service identity, secrets management, key management, authentication, and authorization.
Partner with Security and Engineering teams to deliver secure-by-design solutions, implement Zero Trust principles, and reduce operational friction.
Write high-quality, reliable code, participate in architecture and code reviews, support critical production systems, and drive operational excellence through scalability, resiliency, and automation.
Be part of oncall and incident response of Dev Productivity org.
Skills & Qualifications
5+ years of experience in Cloud Infrastructure, Identity & Access Management (IAM), Identity Engineering, or Security Engineering.
Strong knowledge of authentication, authorization, identity lifecycle management, and federation protocols including SAML, OAuth2, OIDC, SCIM, and RBAC.
Experience designing and operating identity and access controls within AWS environments, with experience building and operating production level services on AWS.
Experience working with container technology.
Experience deploying and operating services on Kubernetes.
Strong automation and coding skills with Python, Go, Terraform, or similar technologies.
A security-first mindset with experience implementing Zero Trust, least-privilege access, and compliance frameworks such as SOC2, FedRAMP, or ITAR.
An product and operational mindset with experience supporting and improving production level services through monitoring, troubleshooting, incident response, and automation.
Excellent collaboration and communication skills, with a proven ability to drive projects and influence technical decisions across teams.
Preferred Skills & Qualifications
Hands-on experience with any Identity platforms - Okta, Microsoft Entra ID (Azure AD), and modern IAM/IGA platforms.
Experiences with Azure and/or GCP is a bonus.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities:\n\n - Design, build, and operate secure, scalable cloud infrastructure and identity platforms in AWS and our own data centers.\n\n - Implement and manage IAM, IGA, authentication, authorization, SSO, MFA, identity lifecycle management, and provisioning/deprovisioning solutions using modern identity platforms and standards such as SAML, OAuth2, OIDC, and SCIM.\n\n - Develop automation, integrations, and infrastructure-as-code solutions using Terraform and programming languages such as Python and Go.\n\n - Design and implement security controls for AI-powered systems, including controlled, audited, and governed agent workflows, while contributing to core security services such as service identity, secrets management, key management, authentication, and authorization.\n\n - Partner with Security and Engineering teams to deliver secure-by-design solutions, implement Zero Trust principles, and reduce operational friction.\n\n - Write high-quality, reliable code, participate in architecture and code reviews, support critical production systems, and drive operational excellence through scalability, resiliency, and automation.\n\n - Be part of oncall and incident response of Dev Productivity org.\n\n\nSkills & Qualifications\n\n - 5+ years of experience in Cloud Infrastructure, Identity & Access Management (IAM), Identity Engineering, or Security Engineering.\n\n - Strong knowledge of authentication, authorization, identity lifecycle management, and federation protocols including SAML, OAuth2, OIDC, SCIM, and RBAC.\n\n - Experience designing and operating identity and access controls within AWS environments, with experience building and operating production level services on AWS.\n\n - Experience working with container technology.\n\n - Experience deploying and operating services on Kubernetes.\n\n - Strong automation and coding skills with Python, Go, Terraform, or similar technologies.\n\n - A security-first mindset with experience implementing Zero Trust, least-privilege access, and compliance frameworks such as SOC2, FedRAMP, or ITAR.\n\n - An product and operational mindset with experience supporting and improving production level services through monitoring, troubleshooting, incident response, and automation.\n\n - Excellent collaboration and communication skills, with a proven ability to drive projects and influence technical decisions across teams.\n\n\nPreferred Skills & Qualifications\n\n - Hands-on experience with any Identity platforms - Okta, Microsoft Entra ID (Azure AD), and modern IAM/IGA platforms.\n\n - Experiences with Azure and/or GCP is a bonus.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"2c786281-e51c-4d2d-a760-2ef907d81760","title":"Director, Strategic Finance - Corporate FP&A","department":"Commercial Operations Departments","team":"Finance","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-05-21T15:19:46.206+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/2c786281-e51c-4d2d-a760-2ef907d81760","applyUrl":"https://jobs.ashbyhq.com/cerebras/2c786281-e51c-4d2d-a760-2ef907d81760/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
This role is a front-row seat in a company at the leading edge of AI compute. You will create the corporate FP&A operating system for the company: long-range planning, annual planning, forecasting, executive reporting, guidance support, and SG&A business partnering that keeps decision-ready insight flowing as the company scales. The scope can stretch for a proven FP&A leader seeking a sharper public-company platform or a high-potential leader ready to pull the function forward from day one. You will work across leadership teams and be accountable for outcomes, not outputs. You will report to the Head of FP&A.
Why now
Cerebras is newly public and scaling at pace. This commercial traction demands exceptional financial operations. This role will be a driver of this capability.
Responsibilities
Ownership: Company-wide corporate FP&A, including owning the company model, leading long-range and annual planning, monthly forecasting, revenue forecasting, G&A budgeting, headcount, spend management, Board reporting, and public-company reporting support.
Operating model: Player-coach on a flat, high-standards team. You bring a track record of building talent-dense teams, use technology to multiply output, and set the bar by staying close to the work.
Success definition: FP&A is the center of context for the organization. The team will deliver investor-grade information to the right partners at the right time.
What you will build
Corporate FP&A infrastructure for a newly public company: planning, forecasting, reporting, guidance support, and G&A spend visibility.
A decision-quality KPI and reporting architecture: scorecards, dashboards, recurring reviews, and crisp narratives that leadership and investors trust.
Financial models leaders can use: clean inputs, stress-tested assumptions, clear outputs, and documented logic across planning, budgeting, forecasts, and guidance support.
A world-class business partnership motion: business leaders rely on the FP&A team for insight. We deliver true partnership, not spreadsheet help
Make order out of chaos. Build mechanisms that turn messy business inputs into repeatable processes including forecasting cadences, metric definitions, reconciliation paths, and accountability loops.
Automation and tooling that compounds output for a small, talent-dense team, including structured data pulls, workflow automation, and pragmatic AI use.
Public-company-ready operating rhythms: clean close-to-insight timelines, clear ownership, guidance support, and durable definitions that scale with scrutiny.
What you will own
G&A business partnering: Serve as the primary finance partner to G&A leadership. Bring structure, speed, and judgment to budgeting, headcount planning, spend management, and strategic investment decisions.
Corporate planning: Own and continuously improve forecasting, budgeting, annual planning, long-range planning, scenario planning, and performance reporting across the company.
Revenue forecasting: Own the company revenue forecast and partner closely with Sales and Product to build accurate, data-driven projections, variance insights, and guidance support.
Executive, Board, and investor reporting: Prepare and deliver financial reporting, insights, and commentary for executive leadership, the Board, investors, and public-market processes.
KPIs and dashboards: Develop and refine KPIs, scorecards, dashboards, and analytical frameworks that highlight trends, track operating leverage, and guide leadership decisions.
Capital allocation and systems: Conduct analysis to support investment decisions and long-term planning, and drive improvements in financial systems, AI-enabled workflows, tools, and data quality.
What success looks like in the first 6 to 12 months
You earn the trust of leadership by delivering the right insights at the right time in the right way.
G&A leaders and executives proactively pull you into decisions because your work improves outcomes, not just visibility.
Durable insight assets are live (dashboards, forecast packs, KPI definitions, Board-ready and investor-ready reporting) with a clear cadence and single-source-of-truth inputs.
The long-range plan, annual operating plan, and monthly forecast process run smoothly, with scenario levers leadership uses for decisions, guidance support, and operating tradeoffs.
G&A spend and headcount visibility improve through better planning discipline, reducing surprises and improving decision quality.
The revenue forecast and variance process are credible, timely, and actionable, with clear ownership and repeatable guidance-support inputs.
You have improved the system: fewer manual consolidations, fewer one-off analyses, and more AI-enabled mechanisms that keep the business informed as scale increases.
What we are looking for
We are hiring for judgment, agency, systems thinking, and player-coach leadership. You know what great FP&A looks like, build what the business needs next, and bring others along.
15+ years of total experience (rough guide), ideally across corporate FP&A, strategic finance, or adjacent roles. We are open to proven Directors and VP-level leaders seeking a high-slope public-company platform.
Corporate FP&A leadership experience, ideally in a public-company or newly public environment, or training from a comparably rigorous analytical setting. You have seen excellent FP&A up close and can raise the bar quickly.
Strong financial modeling skills. You can build from scratch, pressure-test assumptions, and defend outputs with clarity.
Proven G&A and executive-facing partnership. You earn trust by being fast, right, and useful, then scale that trust through repeatable mechanisms.
Player-coach systems thinker. You have built or raised the bar for small, talent-dense teams and can build infrastructure that works as pace increases and data gets messy.
High agency. You operate in ambiguity, move without perfect inputs or direction, close loops, and bring pattern recognition rather than a rigid playbook.
Clear executive communication. You distill complexity into concise narratives, perform grounded root-cause analysis, and influence decisions.
Technical fluency beyond spreadsheets (preferred). Comfortable with Excel, PowerPoint, SQL, Python, AI tools, and planning or BI tooling.
Ways to stand out
Experience in hardware, semiconductor, infrastructure, or other complex businesses with sophisticated revenue and spend planning.
Time at a public, newly public, or high-growth company navigating rapid scale, guidance support, and public-company planning rhythms.
Experience with performance management, scorecards, dashboarding, and operating leverage analysis.
Fluency with planning, ERP, and BI systems (for example NetSuite, Oracle, or Looker) and the practical reality of integrating finance processes across functions.
Strong AI affinity: you apply modern tools to automate work, accelerate analysis, raise quality, and extend small-team output.
Location
In-person at Cerebras headquarters in Sunnyvale, California.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThis role is a front-row seat in a company at the leading edge of AI compute. You will create the corporate FP&A operating system for the company: long-range planning, annual planning, forecasting, executive reporting, guidance support, and SG&A business partnering that keeps decision-ready insight flowing as the company scales. The scope can stretch for a proven FP&A leader seeking a sharper public-company platform or a high-potential leader ready to pull the function forward from day one. You will work across leadership teams and be accountable for outcomes, not outputs. You will report to the Head of FP&A.\n\nWhy now\n\nCerebras is newly public and scaling at pace. This commercial traction demands exceptional financial operations. This role will be a driver of this capability.\n\nResponsibilities\n\n - Ownership: Company-wide corporate FP&A, including owning the company model, leading long-range and annual planning, monthly forecasting, revenue forecasting, G&A budgeting, headcount, spend management, Board reporting, and public-company reporting support.\n\n - Operating model: Player-coach on a flat, high-standards team. You bring a track record of building talent-dense teams, use technology to multiply output, and set the bar by staying close to the work.\n\n - Success definition: FP&A is the center of context for the organization. The team will deliver investor-grade information to the right partners at the right time.\n\nWhat you will build\n\n - Corporate FP&A infrastructure for a newly public company: planning, forecasting, reporting, guidance support, and G&A spend visibility.\n\n - A decision-quality KPI and reporting architecture: scorecards, dashboards, recurring reviews, and crisp narratives that leadership and investors trust.\n\n - Financial models leaders can use: clean inputs, stress-tested assumptions, clear outputs, and documented logic across planning, budgeting, forecasts, and guidance support.\n\n - A world-class business partnership motion: business leaders rely on the FP&A team for insight. We deliver true partnership, not spreadsheet help\n\n - Make order out of chaos. Build mechanisms that turn messy business inputs into repeatable processes including forecasting cadences, metric definitions, reconciliation paths, and accountability loops.\n\n - Automation and tooling that compounds output for a small, talent-dense team, including structured data pulls, workflow automation, and pragmatic AI use.\n\n - Public-company-ready operating rhythms: clean close-to-insight timelines, clear ownership, guidance support, and durable definitions that scale with scrutiny.\n\nWhat you will own\n\n - G&A business partnering: Serve as the primary finance partner to G&A leadership. Bring structure, speed, and judgment to budgeting, headcount planning, spend management, and strategic investment decisions.\n\n - Corporate planning: Own and continuously improve forecasting, budgeting, annual planning, long-range planning, scenario planning, and performance reporting across the company.\n\n - Revenue forecasting: Own the company revenue forecast and partner closely with Sales and Product to build accurate, data-driven projections, variance insights, and guidance support.\n\n - Executive, Board, and investor reporting: Prepare and deliver financial reporting, insights, and commentary for executive leadership, the Board, investors, and public-market processes.\n\n - KPIs and dashboards: Develop and refine KPIs, scorecards, dashboards, and analytical frameworks that highlight trends, track operating leverage, and guide leadership decisions.\n\n - Capital allocation and systems: Conduct analysis to support investment decisions and long-term planning, and drive improvements in financial systems, AI-enabled workflows, tools, and data quality.\n\nWhat success looks like in the first 6 to 12 months\n\n - You earn the trust of leadership by delivering the right insights at the right time in the right way.\n\n - G&A leaders and executives proactively pull you into decisions because your work improves outcomes, not just visibility.\n\n - Durable insight assets are live (dashboards, forecast packs, KPI definitions, Board-ready and investor-ready reporting) with a clear cadence and single-source-of-truth inputs.\n\n - The long-range plan, annual operating plan, and monthly forecast process run smoothly, with scenario levers leadership uses for decisions, guidance support, and operating tradeoffs.\n\n - G&A spend and headcount visibility improve through better planning discipline, reducing surprises and improving decision quality.\n\n - The revenue forecast and variance process are credible, timely, and actionable, with clear ownership and repeatable guidance-support inputs.\n\n - You have improved the system: fewer manual consolidations, fewer one-off analyses, and more AI-enabled mechanisms that keep the business informed as scale increases.\n\nWhat we are looking for\n\nWe are hiring for judgment, agency, systems thinking, and player-coach leadership. You know what great FP&A looks like, build what the business needs next, and bring others along.\n\n - 15+ years of total experience (rough guide), ideally across corporate FP&A, strategic finance, or adjacent roles. We are open to proven Directors and VP-level leaders seeking a high-slope public-company platform.\n\n - Corporate FP&A leadership experience, ideally in a public-company or newly public environment, or training from a comparably rigorous analytical setting. You have seen excellent FP&A up close and can raise the bar quickly.\n\n - Strong financial modeling skills. You can build from scratch, pressure-test assumptions, and defend outputs with clarity.\n\n - Proven G&A and executive-facing partnership. You earn trust by being fast, right, and useful, then scale that trust through repeatable mechanisms.\n\n - Player-coach systems thinker. You have built or raised the bar for small, talent-dense teams and can build infrastructure that works as pace increases and data gets messy.\n\n - High agency. You operate in ambiguity, move without perfect inputs or direction, close loops, and bring pattern recognition rather than a rigid playbook.\n\n - Clear executive communication. You distill complexity into concise narratives, perform grounded root-cause analysis, and influence decisions.\n\n - Technical fluency beyond spreadsheets (preferred). Comfortable with Excel, PowerPoint, SQL, Python, AI tools, and planning or BI tooling.\n\nWays to stand out\n\n - Experience in hardware, semiconductor, infrastructure, or other complex businesses with sophisticated revenue and spend planning.\n\n - Time at a public, newly public, or high-growth company navigating rapid scale, guidance support, and public-company planning rhythms.\n\n - Experience with performance management, scorecards, dashboarding, and operating leverage analysis.\n\n - Fluency with planning, ERP, and BI systems (for example NetSuite, Oracle, or Looker) and the practical reality of integrating finance processes across functions.\n\n - Strong AI affinity: you apply modern tools to automate work, accelerate analysis, raise quality, and extend small-team output.\n\nLocation\n\nIn-person at Cerebras headquarters in Sunnyvale, California.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"3c456e76-308b-4a6b-8e9a-01def6383d28","title":"Staff Site Reliability Engineer – Automation and Platform ","department":"Software","team":"Cloud","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[{"location":"Toronto Office","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2025-10-03T21:18:58.442+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/3c456e76-308b-4a6b-8e9a-01def6383d28","applyUrl":"https://jobs.ashbyhq.com/cerebras/3c456e76-308b-4a6b-8e9a-01def6383d28/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for leading model builders such as OpenAI and other frontier labs.
As a Staff SRE, you will lead the engineering effort to eliminate toil at scale by driving implementation of self-service delivery pipelines, shared observability common tooling. This role starts with ~1 month of hands-on operational immersion to gain deep familiarity with our current stack, production pain points, and high-stakes workflows.
From there, your primary focus shifts to architecting and delivering the \"tomorrow\" layer: declarative GitOps-driven CD for model releases, capacity provisioning and cluster upgrades. Success over the first year in this role will be defined by enabling core teams, product managers, external customers, and cluster stakeholders to operate in a fully self-service model with strong reliability guarantees.
You will partner with our early-career SRE sub-team, who own day-to-day operations. This will allow you to deeply understand their pain points, automate their toil, and mentor them as platform engineers.
You will collaborate with the tech leads and the leadership team across core, cluster, cloud, and product stakeholders. This work will shift reliability from an ops-only burden to a shared engineering discipline that underpins frontier AI inference at scale.
If you are a proven Staff+ engineer who enjoys turning complexity into elegant reliability at scale, this is your chance to lead this transformation from the front.
This role does not require 24/7 on-call rotations.
Key Responsibilities
Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions.
Architect self-service platforms and internal tooling that lets product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs.
Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets; blameless postmortems; chaos testing; and capacity forecasting across multi-datacenter and on-prem environments.
Mentor mid-level SREs, support critical incident escalations, and use production pain points to prioritize the highest-leverage automation work.
Measure and drive impact through clear metrics, including toil reduction, deployment velocity, SLO compliance, MTTR, and adoption of self-service workflows.
Required Experience & Skills
8+ years in SRE, infrastructure engineering, or platform engineering, with a strong record of improving automation and reliability at large scale in FAANG, hyperscaler, or similarly demanding environments.
Deep expertise operating large scale heterogenous clusters with a proprietary cloud control plane
Proven track record designing and delivering CI/CD or GitOps systems using Argo CD or similar tools, with strong safety and observability built in.
Hands-on experience with observability systems such as Loki, Tempo, Mimir, and Prometheus
Ability to lead complex projects end to end, influence cross-functional stakeholders, and communicate technical direction clearly.
Nice-to-Haves
Experience with Bazel or other large-scale build systems in production.
Background in AI/ML inference systems, including model serving runtimes, GPU or wafer-scale orchestration, latency and accuracy SLOs, or drift monitoring.
Prior work on predictive autoscaling, chaos engineering, or cost-aware capacity planning for compute-intensive workloads.
Location
SF Bay Area
Toronto
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for leading model builders such as OpenAI and other frontier labs.\n\nAs a Staff SRE, you will lead the engineering effort to eliminate toil at scale by driving implementation of self-service delivery pipelines, shared observability common tooling. This role starts with ~1 month of hands-on operational immersion to gain deep familiarity with our current stack, production pain points, and high-stakes workflows.\n\nFrom there, your primary focus shifts to architecting and delivering the \"tomorrow\" layer: declarative GitOps-driven CD for model releases, capacity provisioning and cluster upgrades. Success over the first year in this role will be defined by enabling core teams, product managers, external customers, and cluster stakeholders to operate in a fully self-service model with strong reliability guarantees.\n\nYou will partner with our early-career SRE sub-team, who own day-to-day operations. This will allow you to deeply understand their pain points, automate their toil, and mentor them as platform engineers.\n\nYou will collaborate with the tech leads and the leadership team across core, cluster, cloud, and product stakeholders. This work will shift reliability from an ops-only burden to a shared engineering discipline that underpins frontier AI inference at scale.\n\nIf you are a proven Staff+ engineer who enjoys turning complexity into elegant reliability at scale, this is your chance to lead this transformation from the front.\n\nThis role does not require 24/7 on-call rotations.\n\nKey Responsibilities\n\n - Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions.\n\n - Architect self-service platforms and internal tooling that lets product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs.\n\n - Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets; blameless postmortems; chaos testing; and capacity forecasting across multi-datacenter and on-prem environments.\n\n - Mentor mid-level SREs, support critical incident escalations, and use production pain points to prioritize the highest-leverage automation work.\n\n - Measure and drive impact through clear metrics, including toil reduction, deployment velocity, SLO compliance, MTTR, and adoption of self-service workflows.\n\nRequired Experience & Skills\n\n - 8+ years in SRE, infrastructure engineering, or platform engineering, with a strong record of improving automation and reliability at large scale in FAANG, hyperscaler, or similarly demanding environments.\n\n - Deep expertise operating large scale heterogenous clusters with a proprietary cloud control plane\n\n - Proven track record designing and delivering CI/CD or GitOps systems using Argo CD or similar tools, with strong safety and observability built in.\n\n - Hands-on experience with observability systems such as Loki, Tempo, Mimir, and Prometheus\n\n - Ability to lead complex projects end to end, influence cross-functional stakeholders, and communicate technical direction clearly.\n\nNice-to-Haves\n\n - Experience with Bazel or other large-scale build systems in production.\n\n - Background in AI/ML inference systems, including model serving runtimes, GPU or wafer-scale orchestration, latency and accuracy SLOs, or drift monitoring.\n\n - Prior work on predictive autoscaling, chaos engineering, or cost-aware capacity planning for compute-intensive workloads.\n\nLocation\n\n - SF Bay Area\n\n - Toronto\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"3eeb99eb-0998-4fa3-91f6-adae42ea58c3","title":"Senior Product Marketing Manager, AI Inference ","department":"Commercial Operations Departments","team":"Marketing","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-02-24T23:58:18.054+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/3eeb99eb-0998-4fa3-91f6-adae42ea58c3","applyUrl":"https://jobs.ashbyhq.com/cerebras/3eeb99eb-0998-4fa3-91f6-adae42ea58c3/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
The AI conversation moves fast — new models ship weekly, benchmarks shift overnight, and the community's attention resets constantly. Cerebras has a massive speed advantage in inference, and this role exists to make sure that advantage is visible, understood, and top-of-mind wherever developers and AI builders are paying attention.
As Senior Product Marketing Manager, you'll own realtime product marketing for Cerebras inference. You'll create high-impact technical content — blog posts, benchmark analyses, social threads — that positions Cerebras at the center of the AI conversation. You'll find edge in benchmarks, develop new demos that showcase what speed unlocks, and build influencer and community programs that scale our reach beyond what we can do alone. You'll set editorial direction with a high degree of autonomy, reading the market daily and moving as fast as it does. This is a role for someone who lives in the AI ecosystem, uses the tools every day, and knows how to turn a speed advantage into a marketing advantage.
What You'll Own
Realtime Product Marketing
Identify and position Cerebras' edge in a rapidly shifting competitive landscape — identify what matters, what's changing, and where we win
Insert Cerebras into the AI conversation. Create short-form and long-form content that highlights Cerebras' advantage in relation to the most important online conversation around AI (eg. Agents, OpenClaw etc.)
Community & Influencer Marketing
Build programs that generate grassroots community marketing and organic endorsement of Cerebras — through content creators, influencers, and popular software communities
Feature Cerebras in leaderboards and third-party products to showcase our unique product capabilities and leadership position
Marketing Programs & Organic Growth
Develop new and original angles to market both Cerebras capabilities and the success of customers building on our inference
Develop new formats and campaigns that breakthrough in a noisy market and keep Cerebras top-of-mind with technical audiences
Skills And Qualifications
5+ years of product marketing experience in AI, ML infrastructure, or developer tools with a strong portfolio of published technical content
Deep fluency in AI coding models and agentic coding — you understand how these tools work, how developers evaluate them, and what intelligence and speed mean in practice
Hands-on experience benchmarking AI models and producing benchmark content that resonates with technical audiences
Native user of AI coding tools — you use them daily and can create technical artifacts, run evaluations, and build demos independently
Experience building and scaling influencer and content creator programs that drove measurable organic reach
Track record of creating and scaling organic content programs — both first-party and through external contributors
Strong technical writing and editorial judgment — you can tell the story of why speed matters and make it stick
Self-directed and autonomous — you identify what needs to exist, build it, and ship it without waiting for a brief
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThe AI conversation moves fast — new models ship weekly, benchmarks shift overnight, and the community's attention resets constantly. Cerebras has a massive speed advantage in inference, and this role exists to make sure that advantage is visible, understood, and top-of-mind wherever developers and AI builders are paying attention. \n\nAs Senior Product Marketing Manager, you'll own realtime product marketing for Cerebras inference. You'll create high-impact technical content — blog posts, benchmark analyses, social threads — that positions Cerebras at the center of the AI conversation. You'll find edge in benchmarks, develop new demos that showcase what speed unlocks, and build influencer and community programs that scale our reach beyond what we can do alone. You'll set editorial direction with a high degree of autonomy, reading the market daily and moving as fast as it does. This is a role for someone who lives in the AI ecosystem, uses the tools every day, and knows how to turn a speed advantage into a marketing advantage. \n\nWhat You'll Own \n\nRealtime Product Marketing \n\n - Identify and position Cerebras' edge in a rapidly shifting competitive landscape — identify what matters, what's changing, and where we win \n\n - Insert Cerebras into the AI conversation. Create short-form and long-form content that highlights Cerebras' advantage in relation to the most important online conversation around AI (eg. Agents, OpenClaw etc.) \n\nCommunity & Influencer Marketing \n\n - Build programs that generate grassroots community marketing and organic endorsement of Cerebras — through content creators, influencers, and popular software communities \n\n - Feature Cerebras in leaderboards and third-party products to showcase our unique product capabilities and leadership position \n\nMarketing Programs & Organic Growth \n\n - Develop new and original angles to market both Cerebras capabilities and the success of customers building on our inference \n\n - Develop new formats and campaigns that breakthrough in a noisy market and keep Cerebras top-of-mind with technical audiences \n\nSkills And Qualifications \n\n - 5+ years of product marketing experience in AI, ML infrastructure, or developer tools with a strong portfolio of published technical content \n\n - Deep fluency in AI coding models and agentic coding — you understand how these tools work, how developers evaluate them, and what intelligence and speed mean in practice \n\n - Hands-on experience benchmarking AI models and producing benchmark content that resonates with technical audiences \n\n - Native user of AI coding tools — you use them daily and can create technical artifacts, run evaluations, and build demos independently \n\n - Experience building and scaling influencer and content creator programs that drove measurable organic reach \n\n - Track record of creating and scaling organic content programs — both first-party and through external contributors \n\n - Strong technical writing and editorial judgment — you can tell the story of why speed matters and make it stick \n\n - Self-directed and autonomous — you identify what needs to exist, build it, and ship it without waiting for a brief \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"40e0d3ee-8f0a-4b19-9bf9-79410b1c7735","title":"DevOps Engineer - New Grad 2026","department":"Software","team":"Software","employmentType":"FullTime","location":"Toronto Office","secondaryLocations":[],"publishedAt":"2026-05-11T20:00:47.834+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/40e0d3ee-8f0a-4b19-9bf9-79410b1c7735","applyUrl":"https://jobs.ashbyhq.com/cerebras/40e0d3ee-8f0a-4b19-9bf9-79410b1c7735/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As a New Graduate Software Engineer, you will collaborate with world-class engineers to solve real-world challenges across the software stack. You will contribute to software systems that directly impact performance, scalability, reliability, and usability of next-generation AI infrastructure.
You will gain hands-on experience working across multiple layers of a fully integrated AI-accelerated system, including advanced hardware interfaces, low-level infrastructure, distributed systems, compilers, and ML frameworks.
You will develop and maintain the infrastructure required to build, test, operate, simulate, and evaluate the Cerebras software stack. As a DevOps engineer, you will be responsible for designing efficient, scalable workflows for automating processes in the cloud and in our datacenter. You will work closely with the development and product management teams to monitor the quality and performance of the software that runs on the Wafer Scale Engine (WSE), the world’s largest and fastest AI computer.
Required Qualifications
Enrolled in a University program with a degree in Computer Science, Computer Engineering, or other related disciplines.
Experience in software development environments.
Proficient in Python, shell scripting, Makefiles.
Strong end-to-end triage, debug, and troubleshooting skills.
Experience with Jenkins and other CI/CD platforms.
Experience with Docker, Kubernetes and container technology in general.
Experience building services on top of AWS or other cloud platforms at scale.
UI experience highly desirable.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nAs a New Graduate Software Engineer, you will collaborate with world-class engineers to solve real-world challenges across the software stack. You will contribute to software systems that directly impact performance, scalability, reliability, and usability of next-generation AI infrastructure.\n\nYou will gain hands-on experience working across multiple layers of a fully integrated AI-accelerated system, including advanced hardware interfaces, low-level infrastructure, distributed systems, compilers, and ML frameworks.\n\n\nRESPONSIBILITIES\n\nYou will develop and maintain the infrastructure required to build, test, operate, simulate, and evaluate the Cerebras software stack. As a DevOps engineer, you will be responsible for designing efficient, scalable workflows for automating processes in the cloud and in our datacenter. You will work closely with the development and product management teams to monitor the quality and performance of the software that runs on the Wafer Scale Engine (WSE), the world’s largest and fastest AI computer. \n\nRequired Qualifications \n\n - Enrolled in a University program with a degree in Computer Science, Computer Engineering, or other related disciplines. \n\n - Experience in software development environments. \n\n - Proficient in Python, shell scripting, Makefiles. \n\n - Strong end-to-end triage, debug, and troubleshooting skills. \n\n - Experience with Jenkins and other CI/CD platforms. \n\n - Experience with Docker, Kubernetes and container technology in general. \n\n - Experience building services on top of AWS or other cloud platforms at scale. \n\n - UI experience highly desirable. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"4101a058-b42a-4ef0-9b8c-163c0d273509","title":"Senior Quality Engineer","department":"Quality and Reliability","team":"Quality and Reliability","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-04-30T06:54:44.168+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/4101a058-b42a-4ef0-9b8c-163c0d273509","applyUrl":"https://jobs.ashbyhq.com/cerebras/4101a058-b42a-4ef0-9b8c-163c0d273509/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role:
We are looking for a hands-on Senior Quality Engineer to drive manufacturing quality for printed circuit board assemblies (PCBAs), subassemblies, and system-level products across our contract manufacturers and suppliers. This role is responsible for ensuring robust manufacturing processes, superior workmanship, high production yields, and effective corrective actions throughout the product lifecycle.
The ideal candidate brings deep expertise in SMT manufacturing, IPC standards, electronics assembly processes, and statistical quality methods. Working closely with Manufacturing Engineering, Supplier Quality, Reliability Engineering, Design Engineering, and contract manufacturers, you will establish process controls, improve manufacturing capability, and ensure consistent delivery of high-quality products.
While supporting New Product Introduction (NPI) activities as needed, the primary focus of this role is sustaining manufacturing quality, driving continuous improvement, and reducing quality risks in volume production environments.
Manufacturing Quality Execution:
· Serve as the primary quality interface with contract manufacturers; drive alignment on build quality, yield, and corrective actions.
· Lead day-to-day quality activities at the factory floor — audits, line walks, quality gates, outgoing quality checks.
· Monitor SPC charts, AOI/inspection data, and parametric performance to proactively identify and correct drift.
· Coordinate issue containment, corrective action, and verification to closure.
· Own the quality alert process and partner with Engineering to ensure effective disposition of non-conformances.
NPI Quality & Control Plan Strategy:
· Lead NPI quality readiness: establish control plans, process audits, and quality gates for new product builds.
· Partner with Engineering and Manufacturing to translate product requirements into measurable quality controls.
· Proactively identify and de-risk potential failure modes before ramp using PFMEA and design reviews.
· Ensure a smooth handoff from prototype to volume production with stable processes and clear accountability.
Continuous Improvement & Problem-Solving Leadership:
· Act as a pacesetter for problem-solving excellence — driving the consistent use of 8D, 5 Whys, and PFMEA across functions.
· Partner with Reliability Engineering to integrate manufacturing and field data, accelerating detection of systemic issues.
· Identify and prioritize key quality metrics (yield, defect rates, escape rates, first-pass yield) and ensure visibility to stakeholders.
· Support manufacturing change reviews to ensure risks are understood and mitigated before implementation.
Supplier & CM Engagement:
· Work with Supplier Quality to ensure incoming material quality is stable and consistent with outgoing factory performance.
· Build strong working relationships with CM quality teams, establishing clear escalation paths and accountability.
· Participate in supplier audits and quality reviews, feeding learnings back into manufacturing processes.
Skills and Qualifications:
· 7–10+ years of Quality Engineering experience supporting electronics manufacturing, PCBA production, datacenter hardware, networking equipment, semiconductor systems, or similarly complex products.
· Strong knowledge of SMT manufacturing processes including solder paste printing, SPI, pick-and-place, AOI, X-ray inspection, reflow soldering, selective soldering, and final assembly operations.
· Demonstrated expertise with IPC-A-610, J-STD-001, and industry-standard electronics workmanship requirements; IPC certification preferred.
· Experience analyzing ICT, boundary scan, and functional test data to improve yields and reduce manufacturing escapes.
· Proven success driving yield improvement, defect reduction, and process capability improvements in high-volume manufacturing environments.
· Strong understanding of SPC, Cp/Cpk analysis, MSA, DOE, control plans, and manufacturing quality systems.
· Hands-on experience leading root cause investigations and corrective actions using 8D, 5 Whys, PFMEA, and related methodologies.
· Experience working directly with contract manufacturers and EMS providers to improve quality and operational performance.
· Familiarity with failure analysis techniques including X-ray analysis, cross-sections, microscopy, and electrical fault isolation.
The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role: \n\nWe are looking for a hands-on Senior Quality Engineer to drive manufacturing quality for printed circuit board assemblies (PCBAs), subassemblies, and system-level products across our contract manufacturers and suppliers. This role is responsible for ensuring robust manufacturing processes, superior workmanship, high production yields, and effective corrective actions throughout the product lifecycle.\n\nThe ideal candidate brings deep expertise in SMT manufacturing, IPC standards, electronics assembly processes, and statistical quality methods. Working closely with Manufacturing Engineering, Supplier Quality, Reliability Engineering, Design Engineering, and contract manufacturers, you will establish process controls, improve manufacturing capability, and ensure consistent delivery of high-quality products.\n\nWhile supporting New Product Introduction (NPI) activities as needed, the primary focus of this role is sustaining manufacturing quality, driving continuous improvement, and reducing quality risks in volume production environments.\n\nManufacturing Quality Execution: \n\n· Serve as the primary quality interface with contract manufacturers; drive alignment on build quality, yield, and corrective actions. \n\n· Lead day-to-day quality activities at the factory floor — audits, line walks, quality gates, outgoing quality checks. \n\n· Monitor SPC charts, AOI/inspection data, and parametric performance to proactively identify and correct drift. \n\n· Coordinate issue containment, corrective action, and verification to closure. \n\n· Own the quality alert process and partner with Engineering to ensure effective disposition of non-conformances. \n\nNPI Quality & Control Plan Strategy: \n\n· Lead NPI quality readiness: establish control plans, process audits, and quality gates for new product builds. \n\n· Partner with Engineering and Manufacturing to translate product requirements into measurable quality controls. \n\n· Proactively identify and de-risk potential failure modes before ramp using PFMEA and design reviews. \n\n· Ensure a smooth handoff from prototype to volume production with stable processes and clear accountability. \n\nContinuous Improvement & Problem-Solving Leadership: \n\n· Act as a pacesetter for problem-solving excellence — driving the consistent use of 8D, 5 Whys, and PFMEA across functions. \n\n· Partner with Reliability Engineering to integrate manufacturing and field data, accelerating detection of systemic issues. \n\n· Identify and prioritize key quality metrics (yield, defect rates, escape rates, first-pass yield) and ensure visibility to stakeholders. \n\n· Support manufacturing change reviews to ensure risks are understood and mitigated before implementation. \n\nSupplier & CM Engagement: \n\n· Work with Supplier Quality to ensure incoming material quality is stable and consistent with outgoing factory performance. \n\n· Build strong working relationships with CM quality teams, establishing clear escalation paths and accountability. \n\n· Participate in supplier audits and quality reviews, feeding learnings back into manufacturing processes. \n\n \n\nSkills and Qualifications: \n\n· 7–10+ years of Quality Engineering experience supporting electronics manufacturing, PCBA production, datacenter hardware, networking equipment, semiconductor systems, or similarly complex products.\n\n· Strong knowledge of SMT manufacturing processes including solder paste printing, SPI, pick-and-place, AOI, X-ray inspection, reflow soldering, selective soldering, and final assembly operations.\n\n· Demonstrated expertise with IPC-A-610, J-STD-001, and industry-standard electronics workmanship requirements; IPC certification preferred.\n\n· Experience analyzing ICT, boundary scan, and functional test data to improve yields and reduce manufacturing escapes.\n\n· Proven success driving yield improvement, defect reduction, and process capability improvements in high-volume manufacturing environments.\n\n· Strong understanding of SPC, Cp/Cpk analysis, MSA, DOE, control plans, and manufacturing quality systems.\n\n· Hands-on experience leading root cause investigations and corrective actions using 8D, 5 Whys, PFMEA, and related methodologies.\n\n· Experience working directly with contract manufacturers and EMS providers to improve quality and operational performance.\n\n· Familiarity with failure analysis techniques including X-ray analysis, cross-sections, microscopy, and electrical fault isolation.\n\nThe base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"45dec7be-c0c1-40fe-a88d-d13db4f44e42","title":"Design Verification Engineer","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-06-04T18:24:18.201+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/45dec7be-c0c1-40fe-a88d-d13db4f44e42","applyUrl":"https://jobs.ashbyhq.com/cerebras/45dec7be-c0c1-40fe-a88d-d13db4f44e42/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Key Responsibilities
Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works for silicon.
Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.
Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.
Implement tests, manage regressions, gather coverage, and debug test failures.
Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.
Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.
Continuously enhances verification infrastructure and flows to improve efficiency and quality.
Contribute to the evolution of the overall verification methodology and best practices across the organization.
Skills and Qualifications
Great debugging and problem-solving skills.
Deep knowledge of SystemVerilog testbench, DPI and UVM.
Excellent programming skills and knowledge of software engineering practices including object-oriented design.
Experience developing scalable and portable testbenches and components.
Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.
Proficient in scripting languages such as Python or Perl.
Good interpersonal skills and the ability to work as a standout colleague are a must.
Extremely self-motivated and eager to solve problems
3+ years of Design Verification experience.
Desired Skills and Qualifications
Knowledge of pipelined processor architecture.
BS or MS in Computer Science or Electrical Engineering.
3+ years of hands-on Design Verification experience.
Location: Sunnyvale, CA
The base salary range for this position is $190,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nKey Responsibilities\n\n - Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works for silicon.\n\n - Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.\n\n - Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.\n\n - Implement tests, manage regressions, gather coverage, and debug test failures.\n\n - Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.\n\n - Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.\n\n - Continuously enhances verification infrastructure and flows to improve efficiency and quality.\n\n - Contribute to the evolution of the overall verification methodology and best practices across the organization.\n\nSkills and Qualifications\n\n - Great debugging and problem-solving skills.\n\n - Deep knowledge of SystemVerilog testbench, DPI and UVM.\n\n - Excellent programming skills and knowledge of software engineering practices including object-oriented design.\n\n - Experience developing scalable and portable testbenches and components.\n\n - Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.\n\n - Proficient in scripting languages such as Python or Perl.\n\n - Good interpersonal skills and the ability to work as a standout colleague are a must.\n\n - Extremely self-motivated and eager to solve problems\n\n - 3+ years of Design Verification experience.\n\nDesired Skills and Qualifications\n\n - Knowledge of pipelined processor architecture.\n\n - BS or MS in Computer Science or Electrical Engineering.\n\n - 3+ years of hands-on Design Verification experience.\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $190,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"474768a4-7e4f-43c9-a9d3-f23dfe6be406","title":"ML Systems Performance Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-06-16T06:41:30.545+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/474768a4-7e4f-43c9-a9d3-f23dfe6be406","applyUrl":"https://jobs.ashbyhq.com/cerebras/474768a4-7e4f-43c9-a9d3-f23dfe6be406/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.
Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.
Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.
Debug and understand runtime performance on the system and cluster.
Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.
Bachelors / Masters / PhD in Electrical Engineering or Computer Science.
Strong background in computer architecture.
Exposure to and understanding of low-level deep learning / LLM math.
Strong analytical and problem-solving mindset.
3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).
Experience working on CPU/GPU simulators.
Exposure to performance profiling and debug on any system pipeline.
Comfort with C++ and Python.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nEngineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.\n\n\nRESPONSIBILITIES\n\n - Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.\n\n - Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.\n\n - Debug and understand runtime performance on the system and cluster.\n\n - Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.\n\n\nREQUIREMENTS\n\n - Bachelors / Masters / PhD in Electrical Engineering or Computer Science.\n\n - Strong background in computer architecture.\n\n - Exposure to and understanding of low-level deep learning / LLM math.\n\n - Strong analytical and problem-solving mindset.\n\n - 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).\n\n - Experience working on CPU/GPU simulators.\n\n - Exposure to performance profiling and debug on any system pipeline.\n\n - Comfort with C++ and Python.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"4a9ff42b-c834-4445-ba47-2f90d74d83a5","title":"Security & IT General Opportunities","department":"Security Department","team":"Security & IT","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-05-28T20:48:14.601+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/4a9ff42b-c834-4445-ba47-2f90d74d83a5","applyUrl":"https://jobs.ashbyhq.com/cerebras/4a9ff42b-c834-4445-ba47-2f90d74d83a5/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Our IT & Security team sits at the intersection of security, infrastructure, and cutting-edge AI systems. The team plays a critical role in ensuring Cerebras’ environments are secure, reliable, scalable, and ready to support customers operating at the frontier of AI.
We are looking for people who care deeply about operational excellence, security best practices, automation, and building systems that can support a rapidly growing organization.
Depending on the role and team needs, you may contribute to areas such as:
Securing and scaling enterprise IT, cloud, network, and infrastructure environments.
Building automation and tooling to improve security, reliability, and operational efficiency.
Supporting security engineering, detection, response, and vulnerability management efforts.
Improving identity, access, endpoint, network, and systems security practices.
Partnering cross-functionally with IT, Infrastructure, Security, and Engineering teams.
Developing processes and systems that help Cerebras scale securely and efficiently.
Supporting operational rigor across high-impact technical environments.
We are interested in hearing from candidates who:
Think about infrastructure, security, and operations through an automation-first mindset.
Believe that repeatable, scalable systems are better than manual processes.
Care deeply about security, reliability, and operational excellence.
Enjoy working on complex, high-impact systems.
Are comfortable collaborating across IT, Infrastructure, Security, and Engineering teams.
Want to build, improve, and protect systems that support some of the most advanced AI workloads in the world.
Relevant experience may include one or more of the following:
IT Operations or Systems Administration.
Enterprise Security.
Security Engineering.
Network Security.
Systems Security.
Infrastructure Security.
Cloud Security.
Endpoint, Identity, or Access Management.
Security Operations, Detection, or Incident Response.
Automation, scripting, or infrastructure-as-code practices.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nOur IT & Security team sits at the intersection of security, infrastructure, and cutting-edge AI systems. The team plays a critical role in ensuring Cerebras’ environments are secure, reliable, scalable, and ready to support customers operating at the frontier of AI.\n\nWe are looking for people who care deeply about operational excellence, security best practices, automation, and building systems that can support a rapidly growing organization.\n\n\n\n\nRESPONSIBILITIES\n\nDepending on the role and team needs, you may contribute to areas such as:\n\n - Securing and scaling enterprise IT, cloud, network, and infrastructure environments.\n\n - Building automation and tooling to improve security, reliability, and operational efficiency.\n\n - Supporting security engineering, detection, response, and vulnerability management efforts.\n\n - Improving identity, access, endpoint, network, and systems security practices.\n\n - Partnering cross-functionally with IT, Infrastructure, Security, and Engineering teams.\n\n - Developing processes and systems that help Cerebras scale securely and efficiently.\n\n - Supporting operational rigor across high-impact technical environments.\n\n\nSKILLS & QUALIFICATIONS\n\nWe are interested in hearing from candidates who:\n\n - Think about infrastructure, security, and operations through an automation-first mindset.\n\n - Believe that repeatable, scalable systems are better than manual processes.\n\n - Care deeply about security, reliability, and operational excellence.\n\n - Enjoy working on complex, high-impact systems.\n\n - Are comfortable collaborating across IT, Infrastructure, Security, and Engineering teams.\n\n - Want to build, improve, and protect systems that support some of the most advanced AI workloads in the world.\n\n\nPREFERRED SKILLS & QUALIFICATIONS\n\nRelevant experience may include one or more of the following:\n\n - IT Operations or Systems Administration.\n\n - Enterprise Security.\n\n - Security Engineering.\n\n - Network Security.\n\n - Systems Security.\n\n - Infrastructure Security.\n\n - Cloud Security.\n\n - Endpoint, Identity, or Access Management.\n\n - Security Operations, Detection, or Incident Response.\n\n - Automation, scripting, or infrastructure-as-code practices.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"4b52a6d0-93ba-498c-883c-35118cb5b5db","title":"Senior/Staff Engineer : Post Silicon- Bring Up","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-02-16T22:35:43.979+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/4b52a6d0-93ba-498c-883c-35118cb5b5db","applyUrl":"https://jobs.ashbyhq.com/cerebras/4b52a6d0-93ba-498c-883c-35118cb5b5db/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Role:
In this exciting role, you will be responsible for bring up and optimizations of Cerebras’s Wafer Scale Engine (WSE). Suitable candidate will have experience delivering end to end solutions working closely with teams across chip design, system performance, software development and productization.
Responsibilities:
On Wafer Scale Engines, develop and debug flows that embed well tested and deployable optimizations in production processes to reduce time and costs
Work on refining AI Systems across H/W-S/W design constraints such as di/dt, V-F characterization space, current and temperature limits in relation to optimizations for performance.
Develop/Enhance infrastructure to enable silicon for real world workload testing
Develop self-checking metrics, as well as instrumentation for debug and coverage
Work with the silicon architects/designers, performance engineers and software engineers to enhance performance of Wafer Scale Engines.
Work across domains such as, Software, Design, Verification, Emulation & Validation to refine and optimize performance and process.
Work with CI/CD tools, git repositories, github, git actions/Jenkins, merge and release flows to streamline test and release.
Skills & Qualifications:
BS/BE/B.Tech or MS/M.Tech in EE, ECE, CS or equivalent work experience
7-10+ years of industry experience
3-5 years of experience in Pre-silicon & Post Silicon ASIC hardware
Good understanding of computer architecture and networking
Excellent Coding in languages such as Python/Verilog/System Verilog and C
Proficient in hardware/software codesign and layered architectures.
Excellent debugging, analytical, and problem-solving skills
Proficient in large scale testing and automation using pytest and python
Good presentation skills to refine diverse information and put forth optimization strategies and results.
Good interpersonal skills, ability & desire to work as a standout colleague
Proven track record of working cross-functionally learning fast and driving issues to closure
Preferred:
Previous work in AI-ML with 100+ CPU core & communication fabric-based design.
Familiarity with in-line testing and diagnostics using CPU memory and execution with self-checking.
Knowledge of chip defect profiles and mitigation strategies across the hardware and software stack
Familiarity in creating test and s/w infrastructure at large scale
Working across global time zones
Location:
Sunnyvale, California.
Bangalore, India
Toronto, Canada
The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nThe Role:\nIn this exciting role, you will be responsible for bring up and optimizations of Cerebras’s Wafer Scale Engine (WSE). Suitable candidate will have experience delivering end to end solutions working closely with teams across chip design, system performance, software development and productization.\n\n\nResponsibilities:\n\n - On Wafer Scale Engines, develop and debug flows that embed well tested and deployable optimizations in production processes to reduce time and costs \n\n - Work on refining AI Systems across H/W-S/W design constraints such as di/dt, V-F characterization space, current and temperature limits in relation to optimizations for performance.\n\n - Develop/Enhance infrastructure to enable silicon for real world workload testing\n\n - Develop self-checking metrics, as well as instrumentation for debug and coverage\n\n - Work with the silicon architects/designers, performance engineers and software engineers to enhance performance of Wafer Scale Engines.\n\n - Work across domains such as, Software, Design, Verification, Emulation & Validation to refine and optimize performance and process.\n\n - Work with CI/CD tools, git repositories, github, git actions/Jenkins, merge and release flows to streamline test and release.\n\nSkills & Qualifications:\n\n - BS/BE/B.Tech or MS/M.Tech in EE, ECE, CS or equivalent work experience\n\n - 7-10+ years of industry experience\n\n - 3-5 years of experience in Pre-silicon & Post Silicon ASIC hardware\n\n - Good understanding of computer architecture and networking\n\n - Excellent Coding in languages such as Python/Verilog/System Verilog and C\n\n - Proficient in hardware/software codesign and layered architectures.\n\n - Excellent debugging, analytical, and problem-solving skills\n\n - Proficient in large scale testing and automation using pytest and python\n\n - Good presentation skills to refine diverse information and put forth optimization strategies and results.\n\n - Good interpersonal skills, ability & desire to work as a standout colleague\n\n - Proven track record of working cross-functionally learning fast and driving issues to closure \n\nPreferred:\n\n - Previous work in AI-ML with 100+ CPU core & communication fabric-based design.\n\n - Familiarity with in-line testing and diagnostics using CPU memory and execution with self-checking.\n\n - Knowledge of chip defect profiles and mitigation strategies across the hardware and software stack\n\n - Familiarity in creating test and s/w infrastructure at large scale\n\n - Working across global time zones \n\nLocation:\n\nSunnyvale, California.\n\nBangalore, India\n\nToronto, Canada \n\nThe base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"4dd7ad78-80c1-4826-ac4c-8f0371773281","title":"Electrical Engineer","department":"Hardware Departments","team":"Systems","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-02-19T01:59:58.158+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/4dd7ad78-80c1-4826-ac4c-8f0371773281","applyUrl":"https://jobs.ashbyhq.com/cerebras/4dd7ad78-80c1-4826-ac4c-8f0371773281/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities
Lead printed circuit board design through all development stages: from definition to implementation, bring-up, qualification, and production release.
Full responsibility for electrical specification, schematic design, components selection, and layout considerations.
Extensive lab bring-up and debugging, including developing automated benchtop setups for board characterization.
Collaborate with various design and operations teams: manufacturing operations & test engineering, supply chain, ASIC, mechanical, signal integrity, power delivery, layout, embedded & diagnostic, etc.
Skills & Qualifications
B.S.c, M.S.c, or Ph.D. degree in electrical engineering, or equivalent experience.
5 to 10 years of experience as a board design engineer (exceptional candidates with other experience levels will also be considered).
Experience with digital circuits, power delivery, voltage regulators, and high-speed signal integrity.
System-level understanding and familiarity with production environment.
Proficiency with lab/test scripting SW (e.g., Python).
Personal skills: self-instruction, multi-disciplined, multi-tasking and good interpersonal relationship.
The base salary range for this position is $150,000 to $260,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Location: Sunnyvale, California
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities \n\n - Lead printed circuit board design through all development stages: from definition to implementation, bring-up, qualification, and production release. \n\n - Full responsibility for electrical specification, schematic design, components selection, and layout considerations. \n\n - Extensive lab bring-up and debugging, including developing automated benchtop setups for board characterization. \n\n - Collaborate with various design and operations teams: manufacturing operations & test engineering, supply chain, ASIC, mechanical, signal integrity, power delivery, layout, embedded & diagnostic, etc. \n\n \n\nSkills & Qualifications \n\n - B.S.c, M.S.c, or Ph.D. degree in electrical engineering, or equivalent experience. \n\n - 5 to 10 years of experience as a board design engineer (exceptional candidates with other experience levels will also be considered). \n\n - Experience with digital circuits, power delivery, voltage regulators, and high-speed signal integrity. \n\n - System-level understanding and familiarity with production environment. \n\n - Proficiency with lab/test scripting SW (e.g., Python). \n\n - Personal skills: self-instruction, multi-disciplined, multi-tasking and good interpersonal relationship. \n\n \n\nThe base salary range for this position is $150,000 to $260,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nLocation: Sunnyvale, California\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"4e706d0d-65a6-4a36-9ff3-b9e9da16a618","title":"Hardware / Low Level Security Engineer","department":"Security Department","team":"Security & IT","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-06-23T17:24:43.883+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/4e706d0d-65a6-4a36-9ff3-b9e9da16a618","applyUrl":"https://jobs.ashbyhq.com/cerebras/4e706d0d-65a6-4a36-9ff3-b9e9da16a618/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking a Hardware / Low Level Security Engineer to harden the foundational layers of the systems that run the fastest AI inference on earth. You will work close to the metal — across the Linux kernel, firmware, secure boot, and hardware roots of trust — to identify weaknesses, build defenses, and partner with platform and infrastructure teams to ship low-level security improvements. The right candidate brings deep systems expertise, a security mindset shaped by hands-on hardening and exploitation, and a passion for protecting unique compute architectures at scale.
Responsibilities
• Partner with platform, infrastructure, and hardware teams to embed security controls from physical hardware through runtime.
• Design and implement security hardening across the Linux kernel, bootloader, firmware, and host OS layers of Cerebras compute platforms.
• Drive secure boot, measured boot, and attestation strategies across our infrastructure, from the wafer-scale system to supporting host nodes.
• Conduct deep security reviews of kernel modules, drivers, and low-level system components — identifying and remediating memory safety, privilege escalation, and isolation issues.
• Develop kernel-level monitoring and telemetry (e.g., eBPF) to enable detection of low-level attacker behavior.
• Stay ahead of emerging kernel CVEs, supply chain risks, and hardware-level threats — driving response and remediation across the fleet.
• Document low-level security posture, threat models, and remediation playbooks in clear, accessible language.
Skills and Qualifications
• Background in Mechanical and/or Electrical Engineering with career focus in Cybersecurity.
• Deep familiarity with the Linux kernel — including kernel modules, syscall interface, namespaces, cgroups, eBPF, and LSM.
• Hands-on experience with firmware, UEFI, secure boot, TPM, and platform integrity tooling.
• Strong proficiency in C and a modern systems language (Rust, Go, or similar), with the ability to read and write production kernel code.
• Familiarity with hardware-level isolation primitives (e.g., IOMMU, SR-IOV, confidential computing); exposure to non-standard compute architectures a plus.
• Strong written communication skills, with the ability to make low-level security concepts approachable for non-specialists.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n \n\nAbout The Role\n\nWe are seeking a Hardware / Low Level Security Engineer to harden the foundational layers of the systems that run the fastest AI inference on earth. You will work close to the metal — across the Linux kernel, firmware, secure boot, and hardware roots of trust — to identify weaknesses, build defenses, and partner with platform and infrastructure teams to ship low-level security improvements. The right candidate brings deep systems expertise, a security mindset shaped by hands-on hardening and exploitation, and a passion for protecting unique compute architectures at scale.\n\nResponsibilities\n\n• Partner with platform, infrastructure, and hardware teams to embed security controls from physical hardware through runtime.\n\n• Design and implement security hardening across the Linux kernel, bootloader, firmware, and host OS layers of Cerebras compute platforms.\n\n• Drive secure boot, measured boot, and attestation strategies across our infrastructure, from the wafer-scale system to supporting host nodes.\n\n• Conduct deep security reviews of kernel modules, drivers, and low-level system components — identifying and remediating memory safety, privilege escalation, and isolation issues.\n\n• Develop kernel-level monitoring and telemetry (e.g., eBPF) to enable detection of low-level attacker behavior.\n\n• Stay ahead of emerging kernel CVEs, supply chain risks, and hardware-level threats — driving response and remediation across the fleet.\n\n• Document low-level security posture, threat models, and remediation playbooks in clear, accessible language.\n\nSkills and Qualifications\n\n• Background in Mechanical and/or Electrical Engineering with career focus in Cybersecurity.\n\n• Deep familiarity with the Linux kernel — including kernel modules, syscall interface, namespaces, cgroups, eBPF, and LSM.\n\n• Hands-on experience with firmware, UEFI, secure boot, TPM, and platform integrity tooling.\n\n• Strong proficiency in C and a modern systems language (Rust, Go, or similar), with the ability to read and write production kernel code.\n\n• Familiarity with hardware-level isolation primitives (e.g., IOMMU, SR-IOV, confidential computing); exposure to non-standard compute architectures a plus.\n\n• Strong written communication skills, with the ability to make low-level security concepts approachable for non-specialists.\n\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"50e42a6b-89b3-49e9-b907-624447e40d82","title":"Senior Performance Engineer, Inference","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-04-13T14:34:34.293+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/50e42a6b-89b3-49e9-b907-624447e40d82","applyUrl":"https://jobs.ashbyhq.com/cerebras/50e42a6b-89b3-49e9-b907-624447e40d82/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are hiring a Senior Performance Engineer to join our Product team. You are an expert on state-of-the-art inference performance and will serve as our resident expert on how Cerebras stacks up against alternative inference providers on both price and performance. This role sits at the intersection of performance benchmarking from first principles and competitive intelligence. The role has two core pillars:
Performance Benchmarking
You will build, run, and maintain reproducible benchmarks that measure Cerebras inference performance for real customer workloads. This includes metrics like tokens per second, time to first token, latency under concurrency, and total cost of ownership (TCO).
Competitive Pricing Intelligence
You will build and maintain a living model of competitor pricing across the AI inference landscape, including cloud providers, custom silicon vendors, and inference API platforms. You will work directly with our Sales and Product teams to translate this intelligence into pricing recommendations for enterprise contracts, ensuring Cerebras offers a compelling value proposition for every customer.
This role requires deep, hands-on fluency with open-source inference stacks (vLLM, SGLang, TensorRT-LLM), GPU kernel-level optimization toolchains (CUDA, Triton), and an intuitive understanding of how transformer architecture decisions—attention mechanisms, model sizing, quantization, KV-cache strategies—interact with the realities of GPU memory hierarchies and compute budgets.
Design standardized benchmark suites for inference workloads (code generation, summarization, multi-turn conversation, agentic tool use) that enable fair, reproducible comparisons.
Stay current with GPU optimization communities (CUDA, Triton, TensorRT) and evaluate how new kernel fusions, flash-attention variants, and quantization techniques shift performance ceilings.
Build and continuously update a competitive pricing model covering token-based pricing, throughput-based pricing, and enterprise contract structures across major inference providers.
Monitor industry announcements, pricing changes, and new product launches. Synthesize findings into actionable briefs for the Sales and Product teams.
Partner with Sales to build deal-specific competitive analyses showing total cost of ownership and performance advantages for enterprise prospects.
Collaborate with Product and Engineering to identify where competitors are closing gaps or where Cerebras has underappreciated advantages.
Track third-party benchmarking sources (Artificial Analysis, InferenceX) and ensure Cerebras is well-represented and accurately measured.
Required
Deep practical experience with state-of-the-art open-source inference frameworks like vLLM, SGLang, or TensorRT-LLM.
5+ years of experience in ML systems, ML research engineering, or high-performance computing.
Strong understanding of LLM inference economics: tokens, throughput, latency, batch sizes, precision trade-offs, and how these translate to customer cost.
Strong understanding of transformer model architecture internals such as attention mechanisms (MHA, MQA,GQA, MLA, DSA, MHA) and KV-cache management, and how each affects memory and compute profiles.
Self-directed and resourceful.
Preferred
Background in ML research (publications or significant open-source contributions) with a systems or efficiency focus.
Contributions to open-source inference or kernel optimization projects.
Excellent communication skills. You will collaborate with executives, write for engineers, and create materials for sales leaders.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nWe are hiring a Senior Performance Engineer to join our Product team. You are an expert on state-of-the-art inference performance and will serve as our resident expert on how Cerebras stacks up against alternative inference providers on both price and performance. This role sits at the intersection of performance benchmarking from first principles and competitive intelligence. The role has two core pillars:\n\n 1. Performance Benchmarking\n You will build, run, and maintain reproducible benchmarks that measure Cerebras inference performance for real customer workloads. This includes metrics like tokens per second, time to first token, latency under concurrency, and total cost of ownership (TCO). \n \n\n 2. Competitive Pricing Intelligence\n You will build and maintain a living model of competitor pricing across the AI inference landscape, including cloud providers, custom silicon vendors, and inference API platforms. You will work directly with our Sales and Product teams to translate this intelligence into pricing recommendations for enterprise contracts, ensuring Cerebras offers a compelling value proposition for every customer.\n\nThis role requires deep, hands-on fluency with open-source inference stacks (vLLM, SGLang, TensorRT-LLM), GPU kernel-level optimization toolchains (CUDA, Triton), and an intuitive understanding of how transformer architecture decisions—attention mechanisms, model sizing, quantization, KV-cache strategies—interact with the realities of GPU memory hierarchies and compute budgets. \n\n\nRESPONSIBILITIES\n\n - Design standardized benchmark suites for inference workloads (code generation, summarization, multi-turn conversation, agentic tool use) that enable fair, reproducible comparisons. \n\n - Stay current with GPU optimization communities (CUDA, Triton, TensorRT) and evaluate how new kernel fusions, flash-attention variants, and quantization techniques shift performance ceilings. \n\n - Build and continuously update a competitive pricing model covering token-based pricing, throughput-based pricing, and enterprise contract structures across major inference providers. \n\n - Monitor industry announcements, pricing changes, and new product launches. Synthesize findings into actionable briefs for the Sales and Product teams. \n\n - Partner with Sales to build deal-specific competitive analyses showing total cost of ownership and performance advantages for enterprise prospects. \n\n - Collaborate with Product and Engineering to identify where competitors are closing gaps or where Cerebras has underappreciated advantages. \n\n - Track third-party benchmarking sources (Artificial Analysis, InferenceX) and ensure Cerebras is well-represented and accurately measured. \n\n\nSKILLS & QUALIFICATIONS\n\nRequired \n\n - Deep practical experience with state-of-the-art open-source inference frameworks like vLLM, SGLang, or TensorRT-LLM. \n\n - 5+ years of experience in ML systems, ML research engineering, or high-performance computing. \n\n - Strong understanding of LLM inference economics: tokens, throughput, latency, batch sizes, precision trade-offs, and how these translate to customer cost. \n\n - Strong understanding of transformer model architecture internals such as attention mechanisms (MHA, MQA,GQA, MLA, DSA, MHA) and KV-cache management, and how each affects memory and compute profiles. \n\n - Self-directed and resourceful. \n\nPreferred \n\n - Background in ML research (publications or significant open-source contributions) with a systems or efficiency focus. \n\n - Contributions to open-source inference or kernel optimization projects. \n\n - Excellent communication skills. You will collaborate with executives, write for engineers, and create materials for sales leaders. \n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"5301a7ac-75fc-47ed-9194-a0e887ba6531","title":"Software Architect – Manufacturing Test","department":"Hardware Departments","team":"Systems","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-05-26T22:40:08.154+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/5301a7ac-75fc-47ed-9194-a0e887ba6531","applyUrl":"https://jobs.ashbyhq.com/cerebras/5301a7ac-75fc-47ed-9194-a0e887ba6531/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
As the Software Architect for Cerebras' manufacturing test platform, you will lead a team of Full Stack Engineers in designing and delivering the end-to-end software systems that power manufacturing test across every stage of our product lifecycle — from individual components to complete Cerebras systems. The platform spans both cloud infrastructure and physical client-server infrastructure deployed across our manufacturing facilities, and you will own the technical vision, architecture, and roadmap across the full stack. Working closely with hardware design, test engineering, operations, data analytics, and reliability teams, you will translate complex, cross-functional requirements into a cohesive software architecture that drives manufacturing efficiency, quality, and scale.
Responsibilities
Define and own the technical architecture and long-term roadmap for the manufacturing test software platform, including test execution frameworks, user interfaces, distributed data storage, cloud services, on-site client-server systems, and reporting.
Lead, mentor, and grow a team of Full Stack Engineers, setting technical standards for code quality, design patterns, testing, documentation, and operational excellence.
Partner with hardware engineers, test developers, data engineers, operations, and reliability teams to translate business and engineering requirements into clear, scalable software designs.
Drive key architectural decisions across the stack — from front-end frameworks and API design to database schemas, distributed data synchronization, cloud deployments, and on-prem infrastructure across multiple manufacturing facilities.
Conduct design and code reviews, guide technical trade-offs, and ensure the team is building secure, reliable, and maintainable systems.
Collaborate with engineering leadership on planning, prioritization, and delivery commitments, and represent the platform in cross-functional technical discussions.
Identify opportunities to improve manufacturing efficiency, quality, and scalability through better tooling, automation, data infrastructure, and platform capabilities.
Skills and Qualifications
Required
Bachelor's or Master's degree in computer science, computer engineering, or a related field.
8+ years of professional software engineering experience, including 2+ years in a technical leadership, staff engineer, or architect role.
Demonstrated experience designing and delivering complex, full-stack software systems at scale, including distributed systems and data-intensive applications.
Strong proficiency in at least one advanced programming language (e.g. Python, C++) and deep familiarity with modern full-stack development practices.
Experience architecting software for hardware manufacturing environments, such as manufacturing test automation, MES/test data systems, or manufacturing quality control.
Experience architecting and building client-server software, including designing the protocols, APIs, and deployment patterns that connect on-site infrastructure to broader platform services.
Experience with cloud platforms (e.g. AWS, GCP), including infrastructure-as-code, CI/CD, and production operations.
Experience designing systems backed by both SQL databases (e.g. PostgreSQL, MySQL) and NoSQL databases (e.g. MongoDB, Redis), including schema design, performance tuning, and data modeling.
Solid grounding in front-end technologies and frameworks (e.g. HTML, JavaScript, modern UI frameworks) and the ability to make sound architectural decisions about UI/API boundaries.
Track record of mentoring engineers, leading technical projects end-to-end, and partnering effectively with cross-functional stakeholders.
Preferred
Experience building distributed data platforms that synchronize across multiple sites or facilities.
Experience with data engineering, data analytics, and/or business intelligence platforms, and partnering with data teams on reporting and visualization.
Strong UI/UX sensibility and experience guiding the design of tools used by technical operators.
Experience with networking and cybersecurity considerations in industrial or manufacturing settings.
The base salary range for this position is $204,000 to $245,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n\nAbout the Role\n\nAs the Software Architect for Cerebras' manufacturing test platform, you will lead a team of Full Stack Engineers in designing and delivering the end-to-end software systems that power manufacturing test across every stage of our product lifecycle — from individual components to complete Cerebras systems. The platform spans both cloud infrastructure and physical client-server infrastructure deployed across our manufacturing facilities, and you will own the technical vision, architecture, and roadmap across the full stack. Working closely with hardware design, test engineering, operations, data analytics, and reliability teams, you will translate complex, cross-functional requirements into a cohesive software architecture that drives manufacturing efficiency, quality, and scale.\n\n \n\nResponsibilities\n\n - Define and own the technical architecture and long-term roadmap for the manufacturing test software platform, including test execution frameworks, user interfaces, distributed data storage, cloud services, on-site client-server systems, and reporting.\n\n - Lead, mentor, and grow a team of Full Stack Engineers, setting technical standards for code quality, design patterns, testing, documentation, and operational excellence.\n\n - Partner with hardware engineers, test developers, data engineers, operations, and reliability teams to translate business and engineering requirements into clear, scalable software designs.\n\n - Drive key architectural decisions across the stack — from front-end frameworks and API design to database schemas, distributed data synchronization, cloud deployments, and on-prem infrastructure across multiple manufacturing facilities.\n\n - Conduct design and code reviews, guide technical trade-offs, and ensure the team is building secure, reliable, and maintainable systems.\n\n - Collaborate with engineering leadership on planning, prioritization, and delivery commitments, and represent the platform in cross-functional technical discussions.\n\n - Identify opportunities to improve manufacturing efficiency, quality, and scalability through better tooling, automation, data infrastructure, and platform capabilities.\n\nSkills and Qualifications\n\nRequired\n\n - Bachelor's or Master's degree in computer science, computer engineering, or a related field.\n\n - 8+ years of professional software engineering experience, including 2+ years in a technical leadership, staff engineer, or architect role.\n\n - Demonstrated experience designing and delivering complex, full-stack software systems at scale, including distributed systems and data-intensive applications.\n\n - Strong proficiency in at least one advanced programming language (e.g. Python, C++) and deep familiarity with modern full-stack development practices.\n\n - Experience architecting software for hardware manufacturing environments, such as manufacturing test automation, MES/test data systems, or manufacturing quality control.\n\n - Experience architecting and building client-server software, including designing the protocols, APIs, and deployment patterns that connect on-site infrastructure to broader platform services.\n\n - Experience with cloud platforms (e.g. AWS, GCP), including infrastructure-as-code, CI/CD, and production operations.\n\n - Experience designing systems backed by both SQL databases (e.g. PostgreSQL, MySQL) and NoSQL databases (e.g. MongoDB, Redis), including schema design, performance tuning, and data modeling.\n\n - Solid grounding in front-end technologies and frameworks (e.g. HTML, JavaScript, modern UI frameworks) and the ability to make sound architectural decisions about UI/API boundaries.\n\n - Track record of mentoring engineers, leading technical projects end-to-end, and partnering effectively with cross-functional stakeholders.\n\nPreferred\n\n - Experience building distributed data platforms that synchronize across multiple sites or facilities.\n\n - Experience with data engineering, data analytics, and/or business intelligence platforms, and partnering with data teams on reporting and visualization.\n\n - Strong UI/UX sensibility and experience guiding the design of tools used by technical operators.\n\n - Experience with networking and cybersecurity considerations in industrial or manufacturing settings.\n\nThe base salary range for this position is $204,000 to $245,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"538ef11a-dfaa-47f1-8557-790199a769d1","title":"AI Models, Product Manager","department":"Product Management Departments","team":"Product Management","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-01-15T22:47:14.927+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/538ef11a-dfaa-47f1-8557-790199a769d1","applyUrl":"https://jobs.ashbyhq.com/cerebras/538ef11a-dfaa-47f1-8557-790199a769d1/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Own the Future of AI Inference
Cerebras powers the world's fastest AI inference. As the Product Manager for AI Models, you'll lead the strategic model portfolio that defines our product — deciding which models ship, how they perform, and how the world discovers them.
You'll partner directly with leading AI labs, drive launches that shape the industry, and ensure every model on our platform delivers exceptional quality at unprecedented speed.
What You'll Own
Strategic Model Portfolio
Own the models roadmap: decide which frontier and open-source models we support based on market demand, research trends, and strategic fit
Establish partnerships with top model labs, for day0 launches
Build relationships with open-source maintainers to accelerate community model adoption
Product Quality & Customer Success
Define and enforce quality standards across our model catalog through systematic evaluation frameworks
Design benchmarks and evaluations that prove our models deliver production-grade performance
Own the feedback loop: gather customer insights, identify model weaknesses, and drive improvements with engineering
Enable strategic customers to integrate our inference into their products—removing blockers and optimizing for their specific use cases
Go-to-Market Excellence
Lead high-impact model launches that generate buzz and adoption
Create compelling product marketing: demos, benchmarks, tutorials, and documentation that showcase what's possible on Cerebras
Craft technical content that resonates with developers and decision-makers alike
Technical Decision-Making
Select and prioritize performance optimizations (quantization, speculative decoding, etc.) based on customer needs and hardware capabilities
Collaborate with optimization engineers to implement techniques that maximize our speed advantage
Balance tradeoffs between quality, latency, throughput, and cost
Cross-Functional Leadership
Orchestrate launches across model enablement, optimization engineering, deployment, sales, and marketing
Drive alignment in a fast-moving environment where priorities shift based on model releases and customer needs
Be the voice of the customer to engineering and the voice of product to customers
Skills & Qualifications
What we need to see:
5+ years of experience as a product manager, currently at or above the level of Senior PM.
5+ years of total technical work experience (e.g. SWE, ML researcher, solution engineer).
Ability to thrive in a fast-paced, dynamic environment. With an entrepreneurial sense of ownership and ability to lead projects.
Knowledge and passion for the worlds of open-source models and generative AI research.
Knowledge of the community model ecosystem, including: PyTorch, Hugging Face, vLLM, and SGLang.
Highly motivated, independent, organized, and an effective communicator.
Comfortable using Python with the chat completions API, for basic model testing.
Preferred requirements
How to stand out:
Product manager experience at a model training lab or a company that implements open-source models.
Experience working with customers in a solution engineering role.
Experience writing technical marketing assets and social media, with a growing portfolio.
Experience working in a cross-functional organization, and leading projects across multiple teams.
Experience writing model quality evaluations and system prompt harnesses.
Experience writing application code in use cases such as code generation or deep research search application.
Expertise on agentic flows and current LLM model family architectures.
Understanding of model compilers and optimization.
Contributor to communities like vLLM, SGLang, PyTorch, or Hugging Face transformers.
Experience with model optimization or compression methods like quantization.
Location
Hybrid at our Sunnyvale, California or Toronto, Canada office.
Remote possible for candidates willing to travel 1-2x per quarter.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nOwn the Future of AI Inference\n\nCerebras powers the world's fastest AI inference. As the Product Manager for AI Models, you'll lead the strategic model portfolio that defines our product — deciding which models ship, how they perform, and how the world discovers them.\n\nYou'll partner directly with leading AI labs, drive launches that shape the industry, and ensure every model on our platform delivers exceptional quality at unprecedented speed.\n\nWhat You'll Own\n\nStrategic Model Portfolio\n\n - Own the models roadmap: decide which frontier and open-source models we support based on market demand, research trends, and strategic fit\n\n - Establish partnerships with top model labs, for day0 launches\n\n - Build relationships with open-source maintainers to accelerate community model adoption\n\nProduct Quality & Customer Success\n\n - Define and enforce quality standards across our model catalog through systematic evaluation frameworks\n\n - Design benchmarks and evaluations that prove our models deliver production-grade performance\n\n - Own the feedback loop: gather customer insights, identify model weaknesses, and drive improvements with engineering\n\n - Enable strategic customers to integrate our inference into their products—removing blockers and optimizing for their specific use cases\n\nGo-to-Market Excellence\n\n - Lead high-impact model launches that generate buzz and adoption\n\n - Create compelling product marketing: demos, benchmarks, tutorials, and documentation that showcase what's possible on Cerebras\n\n - Craft technical content that resonates with developers and decision-makers alike\n\nTechnical Decision-Making\n\n - Select and prioritize performance optimizations (quantization, speculative decoding, etc.) based on customer needs and hardware capabilities\n\n - Collaborate with optimization engineers to implement techniques that maximize our speed advantage\n\n - Balance tradeoffs between quality, latency, throughput, and cost\n\nCross-Functional Leadership\n\n - Orchestrate launches across model enablement, optimization engineering, deployment, sales, and marketing\n\n - Drive alignment in a fast-moving environment where priorities shift based on model releases and customer needs\n\n - Be the voice of the customer to engineering and the voice of product to customers\n\nSkills & Qualifications \n\nWhat we need to see:\n\n 1. 5+ years of experience as a product manager, currently at or above the level of Senior PM.\n\n 2. 5+ years of total technical work experience (e.g. SWE, ML researcher, solution engineer).\n\n 3. Ability to thrive in a fast-paced, dynamic environment. With an entrepreneurial sense of ownership and ability to lead projects.\n\n 4. Knowledge and passion for the worlds of open-source models and generative AI research.\n\n 5. Knowledge of the community model ecosystem, including: PyTorch, Hugging Face, vLLM, and SGLang.\n\n 6. Highly motivated, independent, organized, and an effective communicator.\n\n 7. Comfortable using Python with the chat completions API, for basic model testing.\n\nPreferred requirements \n\nHow to stand out:\n\n 1. Product manager experience at a model training lab or a company that implements open-source models.\n\n 2. Experience working with customers in a solution engineering role.\n\n 3. Experience writing technical marketing assets and social media, with a growing portfolio.\n\n 4. Experience working in a cross-functional organization, and leading projects across multiple teams.\n\n 5. Experience writing model quality evaluations and system prompt harnesses.\n\n 6. Experience writing application code in use cases such as code generation or deep research search application.\n\n 7. Expertise on agentic flows and current LLM model family architectures.\n\n 8. Understanding of model compilers and optimization.\n\n 9. Contributor to communities like vLLM, SGLang, PyTorch, or Hugging Face transformers.\n\n 10. Experience with model optimization or compression methods like quantization.\n\nLocation \n\n - Hybrid at our Sunnyvale, California or Toronto, Canada office.\n\n - Remote possible for candidates willing to travel 1-2x per quarter. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"58cebd9f-5a5c-4435-843a-aca160d66a32","title":"Principal ML Investigator","department":"Machine Learning Departments","team":"Machine Learning Departments","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2025-12-12T14:22:36.817+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/58cebd9f-5a5c-4435-843a-aca160d66a32","applyUrl":"https://jobs.ashbyhq.com/cerebras/58cebd9f-5a5c-4435-843a-aca160d66a32/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
Cerebras is adding an ML team that can focus on a new ML effort that can align with existing teams. We are seeking a principal investigator who will partner with our ML leaders to formulate the new effort and to build up the new team and capabilities. This new team would coordinate with our current ML teams: Field ML, which works directly with customers, Applied ML, which builds new ML capabilities and applications for customers, and Core ML, which adapts ML algorithms to find unique capabilities of Cerebras hardware. The new team could take up the same or complementary responsibilities.
We would like the new team to work on some of the following areas:
Post-training and reinforcement learning: Techniques used to improve model deployment quality through further training, tuning, RL, and focus on particular downstream tasks;
Dataset curation and optimization: Techniques to collect and select high-quality data, which can help models to train or tune more quickly or to higher quality;
LLM Pretraining: Techniques to ensure stability and compute-efficiency while pretraining high quality models. May include training dynamics, parameterizations, numerics, or others;
Sparsity: Techniques to sparsify models or data that improve training time-to-quality, or optimize inference speed or throughput;
Domains: Coding agents, reasoning agents, generative language, image, video.
Principal Investigator Responsibilities
Build up a team capable of industry research and advanced development.
Organize various advanced development topics into cohesive agenda.
Adapt novel algorithms and model architectures to run on the Cerebras platform.
Systematically train, tune, and evaluate models to guide/advise production scenarios.
Collaborate with other teams to co-design next-generation hardware and software architectures.
Collaborate with external partners (customers, academic) to drive insight and credibility.
Skills & Qualifications
PhD in Computer Science or related field.
Strong grasp of ML theory in one or more of the above areas.
Proven experience engineering ML systems for scale or production deployment.
Experience leading a team of researchers or engineers.
Preferred Skills & Qualifications
Track record of patents or publications in top-tier conferences or journals.
Experience with large language models (e.g., GPT family, Llama).
Experience with distributed training concepts and frameworks.
Experience in training speed optimizations, such as model architecture transformations to target hardware, or low-level kernel development (e.g., Triton).
Ability to analytically model or optimize system performance.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nCerebras is adding an ML team that can focus on a new ML effort that can align with existing teams. We are seeking a principal investigator who will partner with our ML leaders to formulate the new effort and to build up the new team and capabilities. This new team would coordinate with our current ML teams: Field ML, which works directly with customers, Applied ML, which builds new ML capabilities and applications for customers, and Core ML, which adapts ML algorithms to find unique capabilities of Cerebras hardware. The new team could take up the same or complementary responsibilities.\n\nWe would like the new team to work on some of the following areas:\n\n - Post-training and reinforcement learning: Techniques used to improve model deployment quality through further training, tuning, RL, and focus on particular downstream tasks;\n\n - Dataset curation and optimization: Techniques to collect and select high-quality data, which can help models to train or tune more quickly or to higher quality;\n\n - LLM Pretraining: Techniques to ensure stability and compute-efficiency while pretraining high quality models. May include training dynamics, parameterizations, numerics, or others;\n\n - Sparsity: Techniques to sparsify models or data that improve training time-to-quality, or optimize inference speed or throughput;\n\n - Domains: Coding agents, reasoning agents, generative language, image, video.\n\nPrincipal Investigator Responsibilities\n\n - Build up a team capable of industry research and advanced development.\n\n - Organize various advanced development topics into cohesive agenda.\n\n - Adapt novel algorithms and model architectures to run on the Cerebras platform.\n\n - Systematically train, tune, and evaluate models to guide/advise production scenarios.\n\n - Collaborate with other teams to co-design next-generation hardware and software architectures.\n\n - Collaborate with external partners (customers, academic) to drive insight and credibility.\n\nSkills & Qualifications\n\n - PhD in Computer Science or related field.\n\n - Strong grasp of ML theory in one or more of the above areas.\n\n - Proven experience engineering ML systems for scale or production deployment.\n\n - Experience leading a team of researchers or engineers.\n\nPreferred Skills & Qualifications\n\n - Track record of patents or publications in top-tier conferences or journals.\n\n - Experience with large language models (e.g., GPT family, Llama).\n\n - Experience with distributed training concepts and frameworks.\n\n - Experience in training speed optimizations, such as model architecture transformations to target hardware, or low-level kernel development (e.g., Triton).\n\n - Ability to analytically model or optimize system performance.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"594d7525-be2b-4407-8649-6e4a8cd302e8","title":"Applied AI/ML Scientist","department":"Software","team":"Software","employmentType":"FullTime","location":"UAE ","secondaryLocations":[],"publishedAt":"2026-01-14T23:03:59.831+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/594d7525-be2b-4407-8649-6e4a8cd302e8","applyUrl":"https://jobs.ashbyhq.com/cerebras/594d7525-be2b-4407-8649-6e4a8cd302e8/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As an Applied AI Scientist in the FieldML team, you will be responsible for developing and customizing large language models and more broadly large-scale deep learning models to solve specific customer problems. You won't just advise; you will build. You will bridge the gap between state-of-the-art research and real-world applications by helping customers harness the power of the Cerebras Wafer-Scale Engine (WSE) for their AI initiatives.
We are looking for experienced AI Scientists who are passionate about the \"applied\" side of machine learning - those who enjoy not just reading papers, but implementing, training, and scaling models to solve complex business and scientific problems. You will work on a diverse range of projects, from training bespoke models from scratch to fine-tuning and optimizing the latest Large Language Models (LLMs) for specific industry verticals, to designing and building components for custom agentic systems.
The ideal candidate has experience in large model training and/or post-training, a deep understanding of training dynamics and model convergence, and expertise in data curation, combined with strong communication skills.
Key Responsibilities
Customer Use Case Discovery & Project Scoping
Collaborate with customer stakeholders to identify the best approaches to their business problem with AI.
Contribute to the technical scoping of engagements, including feasibility analysis, data quality/availability/readiness assessments, and the selection of optimal model architectures.
Define project milestones, success metrics, and rigorous evaluation benchmarks to ensure the solution delivers measurable value to the customer’s business.
Custom SOTA Models and AI Systems Development
Architect and execute end-to-end training recipes for custom models, tailoring model architecture and training recipes to meet customer-specific performance and accuracy requirements.
Design and implement sophisticated adaptation strategies, including continuous pre-training on private datasets, supervised fine-tuning (SFT), and post-training alignment via RLHF or DPO.
Take full ownership of the training pipeline, from high-performance data preprocessing and tokenization to hyperparameter tuning and loss-curve analysis.
Navigate the nuances of model convergence on specialized hardware, performing deep-dive analysis into loss dynamics and gradient stability.
Scale training workloads across Cerebras clusters, ensuring efficient utilization of the hardware for multi-billion parameter models.
Build and optimize the core components of agentic systems, focusing on tool-use capabilities, long-context reasoning, and multi-step planning.
Technical Customer Leadership
Serve as an AI/ML subject matter expert during technical deep-dives, translating customer requirements into precise training recipes.
Build and maintain strong customer relationships to become their go-to AI/ML expert.
Internal Research and Engineering Collaboration
Act as the \"voice of the customer\" for internal R&D and engineering teams to drive improvements in our software stack and hardware utilization.
Partner with internal ML teams and product teams on prioritization of novel model architectures with Cerebras software stack, development of training recipes and internal case studies.
Distill customer-facing successful projects into internal playbooks, helping scale the FieldML team’s ability to deliver specialized models.
Skills And Qualifications
Education: Master’s or PhD in Computer Science, Machine Learning, or related fields.
Broad Deep Learning Expertise: Expert-level understanding of modern model architectures, including dense transformers, MoEs, multimodal and sequence models, scaling laws and training dynamics.
Hands-on Trainig Experience: Proven track record of training and/or fine-tuning large models (1B+ parameters) and direct experience with the challenges of large-scale model training.
Engineering Proficiency: Mastery of Python and PyTorch, experience with distributed training frameworks and large-scale distributed data processing pipelines and tools.
Strong Interpersonal and Communication Skills: Effective in collaborative and fast-paced team settings, able to work autonomously and within a team in a dynamic environment, managing multiple projects and pivoting as customer needs evolve. Able to present complex technical results to diverse audience - from C-level executives to research scientists, and to work collaboratively to solve customers’ unique challenges.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs an Applied AI Scientist in the FieldML team, you will be responsible for developing and customizing large language models and more broadly large-scale deep learning models to solve specific customer problems. You won't just advise; you will build. You will bridge the gap between state-of-the-art research and real-world applications by helping customers harness the power of the Cerebras Wafer-Scale Engine (WSE) for their AI initiatives. \n\nWe are looking for experienced AI Scientists who are passionate about the \"applied\" side of machine learning - those who enjoy not just reading papers, but implementing, training, and scaling models to solve complex business and scientific problems. You will work on a diverse range of projects, from training bespoke models from scratch to fine-tuning and optimizing the latest Large Language Models (LLMs) for specific industry verticals, to designing and building components for custom agentic systems. \n\nThe ideal candidate has experience in large model training and/or post-training, a deep understanding of training dynamics and model convergence, and expertise in data curation, combined with strong communication skills. \n\nKey Responsibilities \n\n - Customer Use Case Discovery & Project Scoping \n \n - Collaborate with customer stakeholders to identify the best approaches to their business problem with AI. \n \n - Contribute to the technical scoping of engagements, including feasibility analysis, data quality/availability/readiness assessments, and the selection of optimal model architectures. \n \n - Define project milestones, success metrics, and rigorous evaluation benchmarks to ensure the solution delivers measurable value to the customer’s business. \n\n - Custom SOTA Models and AI Systems Development \n \n - Architect and execute end-to-end training recipes for custom models, tailoring model architecture and training recipes to meet customer-specific performance and accuracy requirements. \n \n - Design and implement sophisticated adaptation strategies, including continuous pre-training on private datasets, supervised fine-tuning (SFT), and post-training alignment via RLHF or DPO. \n \n - Take full ownership of the training pipeline, from high-performance data preprocessing and tokenization to hyperparameter tuning and loss-curve analysis. \n \n - Navigate the nuances of model convergence on specialized hardware, performing deep-dive analysis into loss dynamics and gradient stability. \n \n - Scale training workloads across Cerebras clusters, ensuring efficient utilization of the hardware for multi-billion parameter models. \n \n - Build and optimize the core components of agentic systems, focusing on tool-use capabilities, long-context reasoning, and multi-step planning. \n\n - Technical Customer Leadership \n \n - Serve as an AI/ML subject matter expert during technical deep-dives, translating customer requirements into precise training recipes. \n \n - Build and maintain strong customer relationships to become their go-to AI/ML expert. \n\n - Internal Research and Engineering Collaboration \n \n - Act as the \"voice of the customer\" for internal R&D and engineering teams to drive improvements in our software stack and hardware utilization. \n \n - Partner with internal ML teams and product teams on prioritization of novel model architectures with Cerebras software stack, development of training recipes and internal case studies. \n \n - Distill customer-facing successful projects into internal playbooks, helping scale the FieldML team’s ability to deliver specialized models.\n\nSkills And Qualifications \n\n - Education: Master’s or PhD in Computer Science, Machine Learning, or related fields. \n\n - Broad Deep Learning Expertise: Expert-level understanding of modern model architectures, including dense transformers, MoEs, multimodal and sequence models, scaling laws and training dynamics. \n\n - Hands-on Trainig Experience: Proven track record of training and/or fine-tuning large models (1B+ parameters) and direct experience with the challenges of large-scale model training. \n\n - Engineering Proficiency: Mastery of Python and PyTorch, experience with distributed training frameworks and large-scale distributed data processing pipelines and tools. \n\n - Strong Interpersonal and Communication Skills: Effective in collaborative and fast-paced team settings, able to work autonomously and within a team in a dynamic environment, managing multiple projects and pivoting as customer needs evolve. Able to present complex technical results to diverse audience - from C-level executives to research scientists, and to work collaboratively to solve customers’ unique challenges. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"5985b733-1290-4603-8e66-f91c677e99ee","title":"AI Silicon Physical Design Engineer","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2025-04-21T22:48:23.991+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/5985b733-1290-4603-8e66-f91c677e99ee","applyUrl":"https://jobs.ashbyhq.com/cerebras/5985b733-1290-4603-8e66-f91c677e99ee/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
Join our close-knit physical design team where you'll excel in synthesizing, placing, and routing high speed designs. Experience the full spectrum of physical design and implementation, collaborating closely with the RTL team and integrating these blocks seamlessly into the full-chip architecture.
Skills & Qualifications:
10+ years of physical design & physical verification experience.
Strong knowledge of block level and full-chip physical verification methodology.
Strong experience in block/subsystem timing closure.
Expert at optimizing for the best power/performance and area.
Experience with the complete physical design flow.
Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.
Expert with IR/EM analysis and resolution.
Strong background in STA, constraint drafting and timing convergence at block, partition and fullchip.
Should demonstrate and raise the bar for “ownership”, “deep dive” and should demonstrate strong fundamental understanding of PD concepts.
Good understanding of full chip floor planning and integration.
Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.
Demonstrated ability to work with RTL teams to optimize for physical design.
Skills in Design Compiler, Fusion Compiler, ICC2 or similar physical design tools.
BS or MS in Electrical Engineering.
Preferred:
Knowledge of CPU/GPU design a plus.
Block/partition PD, PDV, IR would be good to have.
Knowledge of Synopsys tool suite is a plus.
The salary range for this position is $150,000 – $250,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nJoin our close-knit physical design team where you'll excel in synthesizing, placing, and routing high speed designs. Experience the full spectrum of physical design and implementation, collaborating closely with the RTL team and integrating these blocks seamlessly into the full-chip architecture.\n\n\n\nSkills & Qualifications:\n\n - 10+ years of physical design & physical verification experience.\n\n - Strong knowledge of block level and full-chip physical verification methodology.\n\n - Strong experience in block/subsystem timing closure.\n\n - Expert at optimizing for the best power/performance and area.\n\n - Experience with the complete physical design flow.\n\n - Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.\n\n - Expert with IR/EM analysis and resolution.\n\n - Strong background in STA, constraint drafting and timing convergence at block, partition and fullchip.\n\n - Should demonstrate and raise the bar for “ownership”, “deep dive” and should demonstrate strong fundamental understanding of PD concepts.\n\n - Good understanding of full chip floor planning and integration.\n\n - Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.\n\n - Demonstrated ability to work with RTL teams to optimize for physical design.\n\n - Skills in Design Compiler, Fusion Compiler, ICC2 or similar physical design tools.\n\n - BS or MS in Electrical Engineering.\n\n\n\nPreferred:\n\n - Knowledge of CPU/GPU design a plus.\n\n - Block/partition PD, PDV, IR would be good to have.\n\n - Knowledge of Synopsys tool suite is a plus.\n \n \n\nThe salary range for this position is $150,000 – $250,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"5f0910ab-d750-4dd4-af43-21446237b45c","title":"Staff Software Engineer, Inference Cloud ","department":"Software","team":"Cloud","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2024-07-12T03:15:09.670+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/5f0910ab-d750-4dd4-af43-21446237b45c","applyUrl":"https://jobs.ashbyhq.com/cerebras/5f0910ab-d750-4dd4-af43-21446237b45c/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We're hiring a Staff Engineer to own major areas of the architecture of our Inference Cloud Platform. This team owns the cloud layer behind our Inference Service, with responsibility for availability, latency, reliability, and global scale.
This is a hands-on individual contributor role for an engineer who wants to work on the hardest distributed systems problems in the stack: multi-region traffic architecture, graceful degradation under bursty AI workloads, performance at high QPS, and the operating model for a platform that has to stay fast and available under load. You'll write code, lead key architectural decisions in your domain, debug production issues, and help shape technical direction across adjacent teams.
If you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.
Responsibilities
Platform Direction. Help shape the technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.
Core Cloud Systems. Design and build critical platform components such as service discovery, request routing, load balancing, caching, batching, and traffic management for AI inference workloads.
Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.
Traffic Control & Service Tiers. Define platform mechanisms for admission control, quota management, rate limiting, and differentiated quality of service across workload types and customer tiers.
Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.
Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.
Technical Influence. Partner with ML, Product, Infrastructure, and Platform teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.
Mentorship. Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.
Skills & Qualifications
8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.
Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services.
Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.
Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.
Strong proficiency in backend or systems languages such as Go, C++, or Python, with the expectation that you can contribute production code directly.
Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.
Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.
Preferred Skills & Qualifications
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe're hiring a Staff Engineer to own major areas of the architecture of our Inference Cloud Platform. This team owns the cloud layer behind our Inference Service, with responsibility for availability, latency, reliability, and global scale.\n\nThis is a hands-on individual contributor role for an engineer who wants to work on the hardest distributed systems problems in the stack: multi-region traffic architecture, graceful degradation under bursty AI workloads, performance at high QPS, and the operating model for a platform that has to stay fast and available under load. You'll write code, lead key architectural decisions in your domain, debug production issues, and help shape technical direction across adjacent teams.\n\nIf you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.\n\nResponsibilities\n\n - Platform Direction. Help shape the technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.\n\n - Core Cloud Systems. Design and build critical platform components such as service discovery, request routing, load balancing, caching, batching, and traffic management for AI inference workloads.\n\n - Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.\n\n - Traffic Control & Service Tiers. Define platform mechanisms for admission control, quota management, rate limiting, and differentiated quality of service across workload types and customer tiers.\n\n - Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.\n\n - Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.\n\n - Technical Influence. Partner with ML, Product, Infrastructure, and Platform teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.\n\n - Mentorship. Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.\n\nSkills & Qualifications\n\n - 8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.\n\n - Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services.\n\n - Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.\n\n - Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.\n\n - Strong proficiency in backend or systems languages such as Go, C++, or Python, with the expectation that you can contribute production code directly.\n\n - Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.\n\n - Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.\n\nPreferred Skills & Qualifications\n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"61a88eea-bd78-471c-8088-1ac96f22c88d","title":"Lead Full Stack Machine Learning Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-06-10T07:02:36.144+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/61a88eea-bd78-471c-8088-1ac96f22c88d","applyUrl":"https://jobs.ashbyhq.com/cerebras/61a88eea-bd78-471c-8088-1ac96f22c88d/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
This teams' principal responsibility is to rapidly bring up state-of-the-art open-source models, frameworks and data engineering. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire software stack. Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.
Responsibilities
Contribute to the end-to-end bring up of frameworks for RL, inference serving, ML models on Cerebras CSX systems.
Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.
Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization.
Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups.
Skills & Qualifications
Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field with 10+ years’ experience.
Comfort navigating the full AI toolchain: Python modelling code, compiler IRs, performance profiling, etc.
Strong debugging skills across performance, numerical accuracy, and runtime integration.
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion).
Proficiency in C/C++ programming and experience with low-level optimization.
Strong background in optimization techniques, particularly those involving NP-hard problems.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThis teams' principal responsibility is to rapidly bring up state-of-the-art open-source models, frameworks and data engineering. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire software stack. Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.\n\nResponsibilities\n\n - Contribute to the end-to-end bring up of frameworks for RL, inference serving, ML models on Cerebras CSX systems.\n\n - Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.\n\n - Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization.\n\n - Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups.\n\nSkills & Qualifications\n\n - Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field with 10+ years’ experience.\n\n - Comfort navigating the full AI toolchain: Python modelling code, compiler IRs, performance profiling, etc.\n\n - Strong debugging skills across performance, numerical accuracy, and runtime integration.\n\n - Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion).\n\n - Proficiency in C/C++ programming and experience with low-level optimization.\n\n - Strong background in optimization techniques, particularly those involving NP-hard problems.\n\n\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"62b9ff34-0fcb-414d-ba1f-cf05edd4b164","title":"Regional Data Center Manager - Finland","department":"Hardware Departments","team":"Datacenters","employmentType":"FullTime","location":"Finland Office","secondaryLocations":[],"publishedAt":"2026-06-29T18:51:46.793+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"South Savo","addressCountry":"Finland","addressLocality":"Mikkeli"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/62b9ff34-0fcb-414d-ba1f-cf05edd4b164","applyUrl":"https://jobs.ashbyhq.com/cerebras/62b9ff34-0fcb-414d-ba1f-cf05edd4b164/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Regional Data Center Manager – Finland (Bilingual Required)
Location
Mikkeli (South Savo) Area, Finland (with regional travel)
About The Role
Cerebras Systems is seeking a Regional Data Center Manager to lead operations, deployment execution, and infrastructure performance across our Finland-based and broader European deployments.
This role sits within the AI Infrastructure organization and is responsible for ensuring that high-density AI clusters are built rapidly, operated reliably, and scaled efficiently.
This is a hands-on leadership role requiring:
Practical data center experience.
Strong working knowledge of MEP systems (Mechanical, Electrical, Plumbing).
The ability to interface directly with facility providers;
The ability to execute at a managerial level, leading local teams while translating and enforcing requirements from global HQ engineering and operations teams.
Fluency in both Finnish and English is required. Being conversant in French is highly desirable.
Own end-to-end data center operations across Finland and adjacent EU sites.
Ensure infrastructure meets performance, uptime, and safety requirements.
Act as the regional execution owner, translating HQ standards into site-level implementation.
Lead incident response and escalation for facility and infrastructure issues.
Serve as primary interface with facility providers, landlords, and MEP vendors.
Ensure facilities meet Cerebras requirements across:
Power (UPS, transformers, distribution paths);
Cooling (CDUs, chilled water loops, CRAH/CRAC systems);
Plumbing (flow, pressure, and loop stability).
Validate facility readiness and performance using real-time telemetry (flow rate, temperature, pressure).
Lead regional execution of cluster deployments (5MW modular increments)
Coordinate with global teams to execute:
Site readiness;
Equipment installation;
Commissioning and handoff to operations.
Drive cross-functional alignment between:
Site Operations;
Network Operations;
Cluster Operations.
Manage and develop local data center technicians and site staff.
Ensure local execution aligns with global standards, MoPs, and engineering requirements.
Act as the bridge between HQ and the field, ensuring:
Requirements are clearly communicated;
Execution is consistent and timely.
Required
Bilingual fluency in Finnish and English; French fluency desirable.
5–10+ years of practical data center or critical facility experience.
Strong working knowledge of MEP systems (mechanical, electrical, plumbing).
Proven ability to interface directly with facility providers and vendors.
Experience managing or leading site-level technical teams.
Ability to execute operationally while aligning with centralized/global direction.
Preferred
Experience with high-density or liquid-cooled environments.
Exposure to AI/HPC infrastructure.
Experience in multi-site or regional operations.
Familiarity with structured incident management frameworks (e.g., ITIL).
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nRegional Data Center Manager – Finland (Bilingual Required)\n\nLocation\nMikkeli (South Savo) Area, Finland (with regional travel)\n\nAbout The Role\nCerebras Systems is seeking a Regional Data Center Manager to lead operations, deployment execution, and infrastructure performance across our Finland-based and broader European deployments.\n\nThis role sits within the AI Infrastructure organization and is responsible for ensuring that high-density AI clusters are built rapidly, operated reliably, and scaled efficiently.\n\nThis is a hands-on leadership role requiring:\n\n - Practical data center experience.\n\n - Strong working knowledge of MEP systems (Mechanical, Electrical, Plumbing).\n\n - The ability to interface directly with facility providers;\n \n - The ability to execute at a managerial level, leading local teams while translating and enforcing requirements from global HQ engineering and operations teams.\n\n - Fluency in both Finnish and English is required. Being conversant in French is highly desirable.\n \n\n\nKEY RESPONSIBILITIES\nREGIONAL OPERATIONS & EXECUTION\n\n - Own end-to-end data center operations across Finland and adjacent EU sites.\n\n - Ensure infrastructure meets performance, uptime, and safety requirements.\n\n - Act as the regional execution owner, translating HQ standards into site-level implementation.\n\n - Lead incident response and escalation for facility and infrastructure issues.\n\n\nFACILITY INTERFACE & MEP OVERSIGHT\n\n - Serve as primary interface with facility providers, landlords, and MEP vendors.\n\n - Ensure facilities meet Cerebras requirements across:\n \n - Power (UPS, transformers, distribution paths);\n \n - Cooling (CDUs, chilled water loops, CRAH/CRAC systems);\n \n - Plumbing (flow, pressure, and loop stability).\n\n - Validate facility readiness and performance using real-time telemetry (flow rate, temperature, pressure).\n\n\nBUILD & DEPLOYMENT LEADERSHIP\n\n - Lead regional execution of cluster deployments (5MW modular increments)\n\n - Coordinate with global teams to execute:\n \n - Site readiness;\n \n - Equipment installation;\n \n - Commissioning and handoff to operations.\n\n - Drive cross-functional alignment between:\n \n - Site Operations;\n \n - Network Operations;\n \n - Cluster Operations.\n\n\nTEAM LEADERSHIP & HQ ALIGNMENT\n\n - Manage and develop local data center technicians and site staff.\n\n - Ensure local execution aligns with global standards, MoPs, and engineering requirements.\n\n - Act as the bridge between HQ and the field, ensuring:\n \n - Requirements are clearly communicated;\n \n - Execution is consistent and timely.\n\n\nQUALIFICATIONS\n\nRequired\n\n - Bilingual fluency in Finnish and English; French fluency desirable.\n\n - 5–10+ years of practical data center or critical facility experience.\n\n - Strong working knowledge of MEP systems (mechanical, electrical, plumbing).\n\n - Proven ability to interface directly with facility providers and vendors.\n\n - Experience managing or leading site-level technical teams.\n\n - Ability to execute operationally while aligning with centralized/global direction.\n\nPreferred\n\n - Experience with high-density or liquid-cooled environments.\n\n - Exposure to AI/HPC infrastructure.\n\n - Experience in multi-site or regional operations.\n\n - Familiarity with structured incident management frameworks (e.g., ITIL).\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"6864fdd6-6848-40b8-b9e5-aea11db86b8b","title":"Senior Front End Design Engineer (Microarchitecture)","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-06-04T19:09:29.337+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/6864fdd6-6848-40b8-b9e5-aea11db86b8b","applyUrl":"https://jobs.ashbyhq.com/cerebras/6864fdd6-6848-40b8-b9e5-aea11db86b8b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a senior front-end design engineer, you will be a key part of the world-class team designing and developing the next generations of the Cerebras Wafer Scale Engine (WSE). This role requires deep expertise in RTL design and integration, with a strong focus on delivering high-performance, power-efficient, and scalable solutions. You will collaborate closely with the design verification, physical design, software and system teams to bring innovative semiconductor architectures from concept to production, addressing the unique challenges of building WSE systems.
Responsibilities
Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL development, Synthesis.
Work closely with PD team members for design closure to meet PPA goals.
Work closely with Design verification and DFT teams for achieving the best functional and test coverage.
Work with software and system teams to understand opportunities to deliver optimal performance and feature set for the product.
Debug silicon-level functional, timing, and power issues during bring up.
Requirements
Master’s degree in Computer Science, Electrical Engineering, or equivalent.
Can work in a hybrid work environment.
8+ years of experience in delivering complex, high performance high quality RTL designs.
Experience with Front End Chip integration and third-party IP integration.
Demonstrated experience in networking, high-performance computing, machine learning or related fields.
Proven track record of multiple silicon success.
Experience collaborating with external vendors.
Networking stack experience including TCP/IP, RDMA and Ethernet.
Knowledge of PCIe, CPU interfaces and Serdes technology.
Working knowledge of scripting tools : Python, TCL.
Assets
Experience with FPGA development toolchain, including Place and Route, Floor planning and Timing Analysis is a plus.
Experience managing external ASIC vendor through product development cycle.
Location: Sunnyvale, CA
The base salary range for this position is $250,000 to $300,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\n\nAbout The Role\n\nAs a senior front-end design engineer, you will be a key part of the world-class team designing and developing the next generations of the Cerebras Wafer Scale Engine (WSE). This role requires deep expertise in RTL design and integration, with a strong focus on delivering high-performance, power-efficient, and scalable solutions. You will collaborate closely with the design verification, physical design, software and system teams to bring innovative semiconductor architectures from concept to production, addressing the unique challenges of building WSE systems.\n\n \n\nResponsibilities\n\n - Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL development, Synthesis.\n\n - Work closely with PD team members for design closure to meet PPA goals.\n\n - Work closely with Design verification and DFT teams for achieving the best functional and test coverage.\n\n - Work with software and system teams to understand opportunities to deliver optimal performance and feature set for the product.\n\n - Debug silicon-level functional, timing, and power issues during bring up.\n\nRequirements\n\n - Master’s degree in Computer Science, Electrical Engineering, or equivalent.\n\n - Can work in a hybrid work environment. \n\n - 8+ years of experience in delivering complex, high performance high quality RTL designs.\n\n - Experience with Front End Chip integration and third-party IP integration.\n\n - Demonstrated experience in networking, high-performance computing, machine learning or related fields.\n\n - Proven track record of multiple silicon success.\n\n - Experience collaborating with external vendors.\n\n - Networking stack experience including TCP/IP, RDMA and Ethernet.\n\n - Knowledge of PCIe, CPU interfaces and Serdes technology.\n\n - Working knowledge of scripting tools : Python, TCL.\n\nAssets\n\n - Experience with FPGA development toolchain, including Place and Route, Floor planning and Timing Analysis is a plus.\n\n - Experience managing external ASIC vendor through product development cycle.\n\n\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $250,000 to $300,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"691225e6-aff8-4371-968d-5aa0b5d8637b","title":"Sr./Staff TPM - Inference Capacity","department":"Software","team":"Cloud","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[{"location":"Remote Office","address":null},{"location":"Toronto Office","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-06-29T20:50:26.407+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/691225e6-aff8-4371-968d-5aa0b5d8637b","applyUrl":"https://jobs.ashbyhq.com/cerebras/691225e6-aff8-4371-968d-5aa0b5d8637b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As demand for AI continues to accelerate, intelligent capacity management becomes one of the company's most strategic challenges. Every customer commitment, model launch, and infrastructure investment depends on making the right capacity decisions at the right time.
We're looking for an experienced Technical Program Manager to lead capacity planning and fleet strategy for our Inference Service organization. This is a highly visible role working directly with Engineering, Product, Infrastructure, SRE, Operations, and executive leadership to maximize utilization of one of the world's most advanced AI inference fleets.
Capacity planning and forecasting. Build and maintain the 6 / 12 / 26-week rolling capacity model across every cluster. Work with product team to translate customer contracts and sales pipeline asks into capacity requirements. Forecast model replicas, system-hours, and spares by customer and by model. Reconcile against actuals weekly. Maintain the source-of-truth doc.
New Datacenter Capacity bring-up. Collaborate with datacenter infrastructure and operations teams to support new datacenter bringup and ensure production readiness. Drive engineering efforts and related automation to ensure on-time and quality delivery.
Allocation and cluster placement. Partner closely with the SRE and product team to run the weekly capacity review across different customers/models/clusters. Decide model placement and re-balancing: which customer tenants land where, which clusters absorb new launches, which freezes are in effect etc. Run the weekly capacity and utilization report for the Inference Service leadership. Post capacity allocation, drive downstream tasks w.r.t deploying models across the allocated capacity with SRE team.
Drive capacity planning tool adoption. Partner with console engineering team to drive stakeholder adoption of the inhouse built capacity planning and allocation tool, including user acceptance testing, issue resolution, tracking changes, pilot testing and deployment. In general, Contribute to the continuous process improvement and development of internal capacity management tools.
Incident tracking and postmortems. Proactively identify and mitigate capacity bottlenecks, risks, and dependencies. In case of any SLA drop due to capacity misallocations, drive related resolution and postmortem.
Run weekly capacity planning and daily capacity and deployment tracking with Engineering, product and operations team. Own fleet utilization reporting and forecasting
Drive capacity planning for new customer deployments and major model launches
Drive continuous improvement and stakeholder adoption of new capacity management platform
Drive org level strategic initiatives related to capacity expansion, improving fleet efficiency and maximizing effective utilization of available systems
Lead planning around major infrastructure events including but not limited to new customer commits, new model releases, change to DC/cluster architecture, etc. that impacts capacity and fleet utilization. Update capacity plans and forecasts accordingly.
Maintain Jira EPICs and Confluence pages related to capacity planning, reporting and change management to ensure execution transparency across teams
5+ years of TPM, technical program management, or product operations experience in cloud infrastructure, large-scale ML serving, or hyperscaler capacity planning
Experience leading large cross-functional programs involving Engineering, Product, and Operations
Comfort with the inference serving stack: model replicas, batching, prefill/decode, KV cache, accelerator scheduling
Strong data fluency: SQL, Grafana, basic Python or Flux to pull your own numbers without waiting for an analyst
Track record of running a recurring cross-functional ritual involving senior engineers and LT
Direct experience with AI accelerator fleet operations such as Habana, TPU pods, Inferentia, Trainium
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nAs demand for AI continues to accelerate, intelligent capacity management becomes one of the company's most strategic challenges. Every customer commitment, model launch, and infrastructure investment depends on making the right capacity decisions at the right time.\n\nWe're looking for an experienced Technical Program Manager to lead capacity planning and fleet strategy for our Inference Service organization. This is a highly visible role working directly with Engineering, Product, Infrastructure, SRE, Operations, and executive leadership to maximize utilization of one of the world's most advanced AI inference fleets.\n\n \n\n\nWHAT YOU'LL OWN\n\nCapacity planning and forecasting. Build and maintain the 6 / 12 / 26-week rolling capacity model across every cluster. Work with product team to translate customer contracts and sales pipeline asks into capacity requirements. Forecast model replicas, system-hours, and spares by customer and by model. Reconcile against actuals weekly. Maintain the source-of-truth doc.\n\nNew Datacenter Capacity bring-up. Collaborate with datacenter infrastructure and operations teams to support new datacenter bringup and ensure production readiness. Drive engineering efforts and related automation to ensure on-time and quality delivery.\n\nAllocation and cluster placement. Partner closely with the SRE and product team to run the weekly capacity review across different customers/models/clusters. Decide model placement and re-balancing: which customer tenants land where, which clusters absorb new launches, which freezes are in effect etc. Run the weekly capacity and utilization report for the Inference Service leadership. Post capacity allocation, drive downstream tasks w.r.t deploying models across the allocated capacity with SRE team.\n\nDrive capacity planning tool adoption. Partner with console engineering team to drive stakeholder adoption of the inhouse built capacity planning and allocation tool, including user acceptance testing, issue resolution, tracking changes, pilot testing and deployment. In general, Contribute to the continuous process improvement and development of internal capacity management tools.\n\nIncident tracking and postmortems. Proactively identify and mitigate capacity bottlenecks, risks, and dependencies. In case of any SLA drop due to capacity misallocations, drive related resolution and postmortem.\n\n\n\nKEY RESPONSIBILITIES\n\n - Run weekly capacity planning and daily capacity and deployment tracking with Engineering, product and operations team. Own fleet utilization reporting and forecasting\n\n - Drive capacity planning for new customer deployments and major model launches\n\n - Drive continuous improvement and stakeholder adoption of new capacity management platform\n\n - Drive org level strategic initiatives related to capacity expansion, improving fleet efficiency and maximizing effective utilization of available systems\n\n - Lead planning around major infrastructure events including but not limited to new customer commits, new model releases, change to DC/cluster architecture, etc. that impacts capacity and fleet utilization. Update capacity plans and forecasts accordingly.\n\n - Maintain Jira EPICs and Confluence pages related to capacity planning, reporting and change management to ensure execution transparency across teams\n\n\nQUALIFICATIONS\n\n - 5+ years of TPM, technical program management, or product operations experience in cloud infrastructure, large-scale ML serving, or hyperscaler capacity planning\n\n - Experience leading large cross-functional programs involving Engineering, Product, and Operations\n\n - Comfort with the inference serving stack: model replicas, batching, prefill/decode, KV cache, accelerator scheduling\n\n - Strong data fluency: SQL, Grafana, basic Python or Flux to pull your own numbers without waiting for an analyst\n\n - Track record of running a recurring cross-functional ritual involving senior engineers and LT\n\n - Direct experience with AI accelerator fleet operations such as Habana, TPU pods, Inferentia, Trainium\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"6b089477-8f01-481a-9425-b30363666d4d","title":"Design Verification Engineer","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2025-11-25T21:37:11.101+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/6b089477-8f01-481a-9425-b30363666d4d","applyUrl":"https://jobs.ashbyhq.com/cerebras/6b089477-8f01-481a-9425-b30363666d4d/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Key Responsibilities
Work with architects, designers, post-silicon, and software engineers, to ensure a high-quality design that works for silicon.
Develop and implement verification strategies, detailed tests, and coverage plans based on micro-architecture.
Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.
Implement tests, manage regressions, gather coverage, and debug test failures.
Collaborate with cross-functional teams, including architecture, RTL design, physical design, firmware, and validation.
Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.
Continuously enhances verification infrastructure and flows to improve efficiency and quality.
Contribute to the evolution of the overall verification methodology and best practices across the organization.
Skills and Qualifications
Advanced debugging and problem-solving skills.
Deep knowledge of SystemVerilog testbench, DPI, and UVM.
Excellent programming skills and knowledge of software engineering practices, including object-oriented design.
Experience developing scalable and portable testbenches and components.
Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate-level simulations.
Proficient in scripting languages such as Python or Perl.
Good interpersonal skills and the ability to work as a standout colleague are a must.
Extremely self-motivated and eager to solve problems
3+ years of Design Verification experience.
Desired Skills and Qualifications
Knowledge of pipelined processor architecture.
BS or MS in Computer Science or Electrical Engineering.
3+ years of hands-on Design Verification experience.
The base salary range for this position is $120,000 to $240,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
We are open to remote candidates.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nKey Responsibilities \n\n - Work with architects, designers, post-silicon, and software engineers, to ensure a high-quality design that works for silicon. \n\n - Develop and implement verification strategies, detailed tests, and coverage plans based on micro-architecture. \n\n - Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage. \n\n - Implement tests, manage regressions, gather coverage, and debug test failures. \n\n - Collaborate with cross-functional teams, including architecture, RTL design, physical design, firmware, and validation. \n\n - Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases. \n\n - Continuously enhances verification infrastructure and flows to improve efficiency and quality. \n\n - Contribute to the evolution of the overall verification methodology and best practices across the organization. \n\nSkills and Qualifications \n\n - Advanced debugging and problem-solving skills. \n\n - Deep knowledge of SystemVerilog testbench, DPI, and UVM. \n\n - Excellent programming skills and knowledge of software engineering practices, including object-oriented design. \n\n - Experience developing scalable and portable testbenches and components. \n\n - Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate-level simulations. \n\n - Proficient in scripting languages such as Python or Perl. \n\n - Good interpersonal skills and the ability to work as a standout colleague are a must. \n\n - Extremely self-motivated and eager to solve problems \n\n - 3+ years of Design Verification experience. \n\nDesired Skills and Qualifications \n\n - Knowledge of pipelined processor architecture. \n\n - BS or MS in Computer Science or Electrical Engineering. \n\n - 3+ years of hands-on Design Verification experience. \n\n \n\nThe base salary range for this position is $120,000 to $240,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWe are open to remote candidates.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"6b3651e3-40ac-44ec-b427-68c78a3a7b5d","title":"Manager - Data Center Asset tracking and Accounting","department":"Commercial Operations Departments","team":"Finance","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-04-13T17:34:33.391+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/6b3651e3-40ac-44ec-b427-68c78a3a7b5d","applyUrl":"https://jobs.ashbyhq.com/cerebras/6b3651e3-40ac-44ec-b427-68c78a3a7b5d/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
The Manager will be primarily responsible for tracking and recovery of Cerebras’s data center infrastructure and assets globally through asset end of life. This leadership position requires an organized, highly motivated professional with the ability to drive operational and process improvements. The individual will perform a variety of tasks ranging from routine to complex analysis and play a critical part in asset tracking operations, including asset dispositions, transfers, and periodic cycle counts.
This role requires comfort operating in a fast-paced, evolving environment, where priorities may shift and processes are still being built. The successful candidate will be expected to ramp quickly, close gaps, and contribute immediately, bringing structure, judgment, and execution while helping where needed across the broader finance organization.
You will partner closely with Manufacturing, Supply Chain, FP&A, Deployment, and Engineering to establish scalable costing models, strengthen controls, and support external reporting readiness as the company prepares to operate as a public company.
Responsibilities
Business Process Optimization
Partner with Supply Chain operations to establish best-in-class asset tracking policies, procedures, and internal controls.
Develop expertise and thoroughly understand the features, functionality, and capability of the fixed asset ERP software system and serve as a thought partner to Finance leadership on process redesign
Drive projects effectively in a high-growth, fast-paced environment, balancing strategic leadership with hands-on execution as the business scales.
Data Center asset management and accounting
Own accounting and cost modeling for data center fixed assets, including AI compute systems, servers, networking, power, and cooling infrastructure.
Support processes to ensure all fixed assets are physically or systematically verified and aligned with the Company’s data center infrastructure management system and asset tracking systems
Establish capitalization policies, useful lives, depreciation methods, and impairment assessments.
Lead and coordinate periodic physical inventory and ensure the system records are updated accordingly
Assist with developing and documenting asset accounting processes including asset transfer, cycle count, and disposition procedures in addition to developing and monitoring system controls and procedures
Partner with Infrastructure and FP&A to forecast capital spend and allocation of depreciation expense.
Data Center Lease accounting
Own end-to-end lease accounting under ASC 842, including lease identification, classification, initial measurement, and ongoing remeasurement/modifications.
Manage the lease close process: prepare/review journal entries, reconciliations, rollforwards, and support monthly/quarterly reporting and variance analysis.
Maintain the lease system of record (e.g., LeaseQuery,); ensure data integrity, controls, and timely updates for new leases, amendments, renewals, and terminations.
Partner with Legal, Procurement, and FP&A to review lease terms, assess embedded leases, and ensure accounting conclusions are documented.
Support lease-related disclosures and support external audit/SOX compliance: process documentation, control design/testing, and audit request management.
Drive process improvements and standardization (templates, checklists, policy updates) to scale lease accounting as the portfolio grows.
Compliance, Reporting & IPO Readiness
Ensure compliance with GAAP, SOX, and internal policies.
Support SEC reporting and disclosures related to fixed assets.
Assist with ad-hoc analyses and cross-functional initiatives as needed to support business priorities.
Skills And Qualifications
Bachelor’s degree in Accounting, Finance, or related field (Master’s preferred).
CPA or CMA strongly preferred.
5+ years of combined experience at a Big 4 accounting firm and manufacturing, hardware, or infrastructure-intensive environments
Strong knowledge of GAAP, costing methodologies, and fixed assets policies and procedures.
Demonstrated experience automating processes and activities, including data center asset management
Strong Microsoft Office skills (Excel/PowerPoint/Word/Outlook) required
Experience with expense allocation models and capital-intensive cost structures.
Exposure to asset tracking solutions along with experience ERPs such as Oracle and NetSuite
Personal Attributes
Thrives in fast-paced, high growth, high-ambiguity environments.
Ability to work with high volumes of unstructured data and create appropriate data structures to provide insights
Able to ramp quickly, identify gaps, and take ownership.
Hands-on, detail-oriented, and execution-focused.
Excellent organizational and time management skills with the ability to multi-task
Strong cross-functional communicator with sound judgment.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThe Manager will be primarily responsible for tracking and recovery of Cerebras’s data center infrastructure and assets globally through asset end of life. This leadership position requires an organized, highly motivated professional with the ability to drive operational and process improvements. The individual will perform a variety of tasks ranging from routine to complex analysis and play a critical part in asset tracking operations, including asset dispositions, transfers, and periodic cycle counts.\n\nThis role requires comfort operating in a fast-paced, evolving environment, where priorities may shift and processes are still being built. The successful candidate will be expected to ramp quickly, close gaps, and contribute immediately, bringing structure, judgment, and execution while helping where needed across the broader finance organization.\n\nYou will partner closely with Manufacturing, Supply Chain, FP&A, Deployment, and Engineering to establish scalable costing models, strengthen controls, and support external reporting readiness as the company prepares to operate as a public company.\n\nResponsibilities\n\nBusiness Process Optimization\n\n - Partner with Supply Chain operations to establish best-in-class asset tracking policies, procedures, and internal controls.\n\n - Develop expertise and thoroughly understand the features, functionality, and capability of the fixed asset ERP software system and serve as a thought partner to Finance leadership on process redesign\n\n - Drive projects effectively in a high-growth, fast-paced environment, balancing strategic leadership with hands-on execution as the business scales.\n\nData Center asset management and accounting\n\n - Own accounting and cost modeling for data center fixed assets, including AI compute systems, servers, networking, power, and cooling infrastructure.\n\n - Support processes to ensure all fixed assets are physically or systematically verified and aligned with the Company’s data center infrastructure management system and asset tracking systems\n\n - Establish capitalization policies, useful lives, depreciation methods, and impairment assessments.\n\n - Lead and coordinate periodic physical inventory and ensure the system records are updated accordingly\n\n - Assist with developing and documenting asset accounting processes including asset transfer, cycle count, and disposition procedures in addition to developing and monitoring system controls and procedures\n\n - Partner with Infrastructure and FP&A to forecast capital spend and allocation of depreciation expense.\n\nData Center Lease accounting\n\n - Own end-to-end lease accounting under ASC 842, including lease identification, classification, initial measurement, and ongoing remeasurement/modifications.\n\n - Manage the lease close process: prepare/review journal entries, reconciliations, rollforwards, and support monthly/quarterly reporting and variance analysis.\n\n - Maintain the lease system of record (e.g., LeaseQuery,); ensure data integrity, controls, and timely updates for new leases, amendments, renewals, and terminations.\n\n - Partner with Legal, Procurement, and FP&A to review lease terms, assess embedded leases, and ensure accounting conclusions are documented.\n\n - Support lease-related disclosures and support external audit/SOX compliance: process documentation, control design/testing, and audit request management.\n\n - Drive process improvements and standardization (templates, checklists, policy updates) to scale lease accounting as the portfolio grows.\n\nCompliance, Reporting & IPO Readiness\n\n - Ensure compliance with GAAP, SOX, and internal policies.\n\n - Support SEC reporting and disclosures related to fixed assets.\n\n - Assist with ad-hoc analyses and cross-functional initiatives as needed to support business priorities.\n\nSkills And Qualifications \n\n - Bachelor’s degree in Accounting, Finance, or related field (Master’s preferred).\n\n - CPA or CMA strongly preferred.\n\n - 5+ years of combined experience at a Big 4 accounting firm and manufacturing, hardware, or infrastructure-intensive environments\n\n - Strong knowledge of GAAP, costing methodologies, and fixed assets policies and procedures.\n\n - Demonstrated experience automating processes and activities, including data center asset management\n\n - Strong Microsoft Office skills (Excel/PowerPoint/Word/Outlook) required\n\n - Experience with expense allocation models and capital-intensive cost structures.\n\n - Exposure to asset tracking solutions along with experience ERPs such as Oracle and NetSuite\n\nPersonal Attributes\n\n - Thrives in fast-paced, high growth, high-ambiguity environments.\n\n - Ability to work with high volumes of unstructured data and create appropriate data structures to provide insights\n\n - Able to ramp quickly, identify gaps, and take ownership.\n\n - Hands-on, detail-oriented, and execution-focused.\n\n - Excellent organizational and time management skills with the ability to multi-task\n\n - Strong cross-functional communicator with sound judgment.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"6d966c0a-d587-4a16-bf57-cfb4b4eb7eef","title":"Senior/Staff- Engineer: Post Silicon- Bring Up ","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-02-16T22:19:16.198+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/6d966c0a-d587-4a16-bf57-cfb4b4eb7eef","applyUrl":"https://jobs.ashbyhq.com/cerebras/6d966c0a-d587-4a16-bf57-cfb4b4eb7eef/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
In this exciting role, you will be responsible for bring up and optimizations of Cerebras’s Wafer Scale Engine (WSE). Suitable candidate will have experience delivering end to end solutions working closely with teams across chip design, system performance, software development and productization.
Responsibilities:
On Wafer Scale Engines, develop and debug flows that embed well tested and deployable optimizations in production processes to reduce time and costs
Work on refining AI Systems across H/W-S/W design constraints such as di/dt, V-F characterization space, current and temperature limits in relation to optimizations for performance.
Develop/Enhance infrastructure to enable silicon for real world workload testing
Develop self-checking metrics, as well as instrumentation for debug and coverage
Work with the silicon architects/designers, performance engineers and software engineers to enhance performance of Wafer Scale Engines.
Work across domains such as, Software, Design, Verification, Emulation & Validation to refine and optimize performance and process.
Work with CI/CD tools, git repositories, github, git actions/Jenkins, merge and release flows to streamline test and release.
Skills & Qualifications:
BS/BE/B.Tech or MS/M.Tech in EE, ECE, CS or equivalent work experience
7-10+ years of industry experience
3-5 years of experience in Pre-silicon & Post Silicon ASIC hardware
Good understanding of computer architecture and networking
Excellent Coding in languages such as Python/Verilog/System Verilog and C
Proficient in hardware/software codesign and layered architectures.
Excellent debugging, analytical, and problem-solving skills
Proficient in large scale testing and automation using pytest and python
Good presentation skills to refine diverse information and put forth optimization strategies and results.
Good interpersonal skills, ability & desire to work as a standout colleague
Proven track record of working cross-functionally learning fast and driving issues to closure
Preferred:
Previous work in AI-ML with 100+ CPU core & communication fabric-based design.
Familiarity with in-line testing and diagnostics using CPU memory and execution with self-checking.
Knowledge of chip defect profiles and mitigation strategies across the hardware and software stack
Familiarity in creating test and s/w infrastructure at large scale
Working across global time zones
Location:
Bangalore, India
Toronto, Canada
Sunnyvale, California.
For Sunnyvale: The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\nIn this exciting role, you will be responsible for bring up and optimizations of Cerebras’s Wafer Scale Engine (WSE). Suitable candidate will have experience delivering end to end solutions working closely with teams across chip design, system performance, software development and productization.\n\n\nResponsibilities:\n\n - On Wafer Scale Engines, develop and debug flows that embed well tested and deployable optimizations in production processes to reduce time and costs \n\n - Work on refining AI Systems across H/W-S/W design constraints such as di/dt, V-F characterization space, current and temperature limits in relation to optimizations for performance.\n\n - Develop/Enhance infrastructure to enable silicon for real world workload testing\n\n - Develop self-checking metrics, as well as instrumentation for debug and coverage\n\n - Work with the silicon architects/designers, performance engineers and software engineers to enhance performance of Wafer Scale Engines.\n\n - Work across domains such as, Software, Design, Verification, Emulation & Validation to refine and optimize performance and process.\n\n - Work with CI/CD tools, git repositories, github, git actions/Jenkins, merge and release flows to streamline test and release.\n\nSkills & Qualifications:\n\n - BS/BE/B.Tech or MS/M.Tech in EE, ECE, CS or equivalent work experience\n\n - 7-10+ years of industry experience\n\n - 3-5 years of experience in Pre-silicon & Post Silicon ASIC hardware\n\n - Good understanding of computer architecture and networking\n\n - Excellent Coding in languages such as Python/Verilog/System Verilog and C\n\n - Proficient in hardware/software codesign and layered architectures.\n\n - Excellent debugging, analytical, and problem-solving skills\n\n - Proficient in large scale testing and automation using pytest and python\n\n - Good presentation skills to refine diverse information and put forth optimization strategies and results.\n\n - Good interpersonal skills, ability & desire to work as a standout colleague\n\n - Proven track record of working cross-functionally learning fast and driving issues to closure \n\nPreferred:\n\n - Previous work in AI-ML with 100+ CPU core & communication fabric-based design.\n\n - Familiarity with in-line testing and diagnostics using CPU memory and execution with self-checking.\n\n - Knowledge of chip defect profiles and mitigation strategies across the hardware and software stack\n\n - Familiarity in creating test and s/w infrastructure at large scale\n\n - Working across global time zones \n\nLocation:\nBangalore, India\n\nToronto, Canada\n\nSunnyvale, California.\n\n \n\nFor Sunnyvale: The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"74ebd69b-14e3-4492-9232-847dd2b77bfa","title":"Mechanical Engineer","department":"Hardware Departments","team":"Systems","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-05-29T00:48:14.145+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/74ebd69b-14e3-4492-9232-847dd2b77bfa","applyUrl":"https://jobs.ashbyhq.com/cerebras/74ebd69b-14e3-4492-9232-847dd2b77bfa/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Mechanical Engineer at Cerebras, you will lead the design of mechanical systems for our next-generation wafer-scale engine. Your responsibilities will include ensuring compliance with specifications, validating manufacturability, and delivering a high-quality product in a fast-paced environment—tackling some of the most challenging problems in the rapidly evolving AI space.
In this role, you will develop mechanical infrastructure for Cerebras’ custom hardware system.
Rapidly iterate on designs and analysis to inform high level systems trades and steer overall product direction.
Provide comprehensive support for environmental and performance testing on hardware, validating analyses, and ensuring compliance with design criteria.
Ownership of technical deliverables within schedules.
Conduct first article inspections, functional analysis, identify and resolve issues
Collaborate across design-manufacturing-production, diagnostic and embedded software engineering teams, contractors and suppliers
Perform detailed structural analysis to engineer robust hardware.
Responsibilities:
Work in a fast paced, high energy environment with short product development cycles on many challenging electro-mechanical projects
Drive and own all design aspects of electro-mechanical systems from concept to bring-up and production
Work with cross functional teams to gather all design requirements to lead the mechanical design, troubleshoot, and create & release all deliverables including drawings, BOMs, etc.
Work closely with thermal engineers to solve mechanical challenges
Evaluate materials and components to meet performance, schedule and cost targets
Work closely with vendors to resolve any DFM/A issues quickly
Requirements:
5+ years of experience as a Mechanical Design Engineer
BS in Mechanical Engineering
Strong analytical, diagnostic and problem-solving skills
Very strong in 3D solids modeling CAD package, proficiency with Solidworks would be preferable
Proficient with PLM system, such as Arena or Agile
Proficient in CTF dimensioning and GD&T
Must be able to do full Tolerance Analysis of complex systems and have working knowledge of FEA
Great team player with strong interpersonal & communication skills
Experience in electronic liquid cooling is a plus
Must have in-depth knowledge of all latest fabrication processes; sheet metal, machining, die-casting, injection molding, and 3D printing
The base salary range for this position is $180,000 to $200,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Mechanical Engineer at Cerebras, you will lead the design of mechanical systems for our next-generation wafer-scale engine. Your responsibilities will include ensuring compliance with specifications, validating manufacturability, and delivering a high-quality product in a fast-paced environment—tackling some of the most challenging problems in the rapidly evolving AI space.\n\nIn this role, you will develop mechanical infrastructure for Cerebras’ custom hardware system.\n\n - Rapidly iterate on designs and analysis to inform high level systems trades and steer overall product direction.\n\n - Provide comprehensive support for environmental and performance testing on hardware, validating analyses, and ensuring compliance with design criteria.\n\n - Ownership of technical deliverables within schedules.\n\n - Conduct first article inspections, functional analysis, identify and resolve issues\n\n - Collaborate across design-manufacturing-production, diagnostic and embedded software engineering teams, contractors and suppliers\n\n - Perform detailed structural analysis to engineer robust hardware.\n\nResponsibilities:\n\n - Work in a fast paced, high energy environment with short product development cycles on many challenging electro-mechanical projects\n\n - Drive and own all design aspects of electro-mechanical systems from concept to bring-up and production\n\n - Work with cross functional teams to gather all design requirements to lead the mechanical design, troubleshoot, and create & release all deliverables including drawings, BOMs, etc.\n\n - Work closely with thermal engineers to solve mechanical challenges\n\n - Evaluate materials and components to meet performance, schedule and cost targets\n\n - Work closely with vendors to resolve any DFM/A issues quickly\n\nRequirements:\n\n - 5+ years of experience as a Mechanical Design Engineer\n\n - BS in Mechanical Engineering\n\n - Strong analytical, diagnostic and problem-solving skills\n\n - Very strong in 3D solids modeling CAD package, proficiency with Solidworks would be preferable\n\n - Proficient with PLM system, such as Arena or Agile\n\n - Proficient in CTF dimensioning and GD&T \n\n - Must be able to do full Tolerance Analysis of complex systems and have working knowledge of FEA\n\n - Great team player with strong interpersonal & communication skills\n\n - Experience in electronic liquid cooling is a plus\n\n - Must have in-depth knowledge of all latest fabrication processes; sheet metal, machining, die-casting, injection molding, and 3D printing\n\nThe base salary range for this position is $180,000 to $200,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"758805c1-fcbf-45c5-93c8-4e92155b570b","title":"Security SWE","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-03-11T18:11:20.970+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/758805c1-fcbf-45c5-93c8-4e92155b570b","applyUrl":"https://jobs.ashbyhq.com/cerebras/758805c1-fcbf-45c5-93c8-4e92155b570b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a frontend engineer on our AI cloud, you will work on our customer-facing inference, training, and admin consoles and API experiences. In this role, you will be responsible for designing and building responsive, user-friendly frontend interfaces that provide an optimal experience for our developers, handling high traffic and throughput efficiently.
Your familiarity with the latest web development frameworks and best practices, coupled with a keen eye for design and user experience, will drive team success.
We're looking for talented software engineers who thrive in ambiguity, view change as an opportunity, and have a voracious desire to learn and share knowledge clearly and concisely.
Skills And Qualifications
5+ years as an individual contributor developing production-grade web frontend products and experiences.
Deep experience with web technologies such as NextJS, React, and TailwindCSS.
Familiarity with backend technologies such as Prisma, PostgreSQL, and Auth.js.
Experience with building high-reliability, production-grade cloud solutions.
Familiarity with architecting and developing advanced web applications.
Strong problem-solving skills and the ability to thrive in ambiguous, rapidly changing conditions.
Excellent communication skills and a passion for continuous learning and knowledge sharing.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a frontend engineer on our AI cloud, you will work on our customer-facing inference, training, and admin consoles and API experiences. In this role, you will be responsible for designing and building responsive, user-friendly frontend interfaces that provide an optimal experience for our developers, handling high traffic and throughput efficiently. \n\nYour familiarity with the latest web development frameworks and best practices, coupled with a keen eye for design and user experience, will drive team success. \n\nWe're looking for talented software engineers who thrive in ambiguity, view change as an opportunity, and have a voracious desire to learn and share knowledge clearly and concisely. \n\nSkills And Qualifications \n\n - 5+ years as an individual contributor developing production-grade web frontend products and experiences. \n\n - Deep experience with web technologies such as NextJS, React, and TailwindCSS. \n\n - Familiarity with backend technologies such as Prisma, PostgreSQL, and Auth.js. \n\n - Experience with building high-reliability, production-grade cloud solutions. \n\n - Familiarity with architecting and developing advanced web applications. \n\n - Strong problem-solving skills and the ability to thrive in ambiguous, rapidly changing conditions. \n\n - Excellent communication skills and a passion for continuous learning and knowledge sharing. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"78c170fd-d494-400b-84c5-3a68d1c03e12","title":"Staff Python / PyTorch Developer — Frontend Inference Compiler – Dubai","department":"Software","team":"Software","employmentType":"FullTime","location":"UAE ","secondaryLocations":[],"publishedAt":"2025-10-31T01:38:25.952+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/78c170fd-d494-400b-84c5-3a68d1c03e12","applyUrl":"https://jobs.ashbyhq.com/cerebras/78c170fd-d494-400b-84c5-3a68d1c03e12/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
The Inference ML Engineering team at Cerebras Systems is dedicated to enabling our fast generative inference solution through simple APIs powered by a distributed runtime that runs on large clusters of our own hardware. Our mission is to empower enterprises, developers, and researchers to unlock the full potential of our platform, leveraging its performance, scalability, and flexibility.
As a Senior Software Engineer on the Inference ML Engineering team, you will design and implement APIs, machine learning features, and tools that enable state-of-the-art generative AI models to run efficiently on our custom hardware. You will collaborate with cross-functional teams to build scalable, high-performance inference solutions while helping shape the evolution of our ML ecosystem.
Responsibilities
Drive and provide technical guidance to a team of software engineers working on complex machine learning integration projects.
Design and implement ML features (e.g., structured outputs, biased sampling, predicted outputs) that improve performance of generative AI models at inference time.
Design and implement high-throughput, low-latency multimodal inference models that support delivery of image, audio, and video inputs and outputs.
Maintain our scalable serving backend for handling many concurrent requests per minute.
Scale our inference service by implementing detailed observability throughout the entire stack.
Analyze and improve latency, throughput, memory usage, and compute efficiency on the service and the implementation of various features.
Optimize software to accelerate generative LLM inference by achieving high throughput and low latency.
Stay up-to-date with advancements in machine learning and deep learning, and apply state-of-the-art techniques to enhance our solutions.
Evaluate trade-offs between different approaches, clearly articulate design choices, and develop detailed proposals for implementing new features.
Uncover, scope, and prioritize significant areas of technical debt across the software stack to ensure continued high quality of the inference service.
Build and maintain robust automated test suites to ensure software quality, performance, and reliability.
Contribute to an agile team environment by delivering high-quality software and adhering to agile development practices.
Lead cross-functional initiatives across the company to deliver high-quality inference solutions.
Skills & Qualifications
Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Mathematics, or a related field.
8+ years of experience in large-scale software engineering, with a focus on deep learning or related domains.
Proficiency in Python for building and maintaining scalable systems.
Advanced proficiency in C++, with an emphasis on multi-threaded programming, performance optimization, and system-level development.
Demonstrated experience driving cross-functional projects.
Experience building and scaling large-scale inference systems for LLMs or multimodal models.
Familiarity with LLM serving frameworks, such as vLLM, SGLang, and TensorRT-LLM.
Solid understanding of software architectural patterns for large-scale, high-performance applications.
Hands-on experience with ML frameworks, such as PyTorch, and a strong understanding of their underlying architectures.
Strong problem-solving skills, with the ability to balance technical depth with practical implementation constraints.
Exceptional communication and presentation skills, with the ability to work both independently and collaboratively across multidisciplinary teams.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nThe Inference ML Engineering team at Cerebras Systems is dedicated to enabling our fast generative inference solution through simple APIs powered by a distributed runtime that runs on large clusters of our own hardware. Our mission is to empower enterprises, developers, and researchers to unlock the full potential of our platform, leveraging its performance, scalability, and flexibility.\n\nAs a Senior Software Engineer on the Inference ML Engineering team, you will design and implement APIs, machine learning features, and tools that enable state-of-the-art generative AI models to run efficiently on our custom hardware. You will collaborate with cross-functional teams to build scalable, high-performance inference solutions while helping shape the evolution of our ML ecosystem.\n\nResponsibilities\n\n - Drive and provide technical guidance to a team of software engineers working on complex machine learning integration projects.\n\n - Design and implement ML features (e.g., structured outputs, biased sampling, predicted outputs) that improve performance of generative AI models at inference time.\n\n - Design and implement high-throughput, low-latency multimodal inference models that support delivery of image, audio, and video inputs and outputs.\n\n - Maintain our scalable serving backend for handling many concurrent requests per minute.\n\n - Scale our inference service by implementing detailed observability throughout the entire stack.\n\n - Analyze and improve latency, throughput, memory usage, and compute efficiency on the service and the implementation of various features.\n\n - Optimize software to accelerate generative LLM inference by achieving high throughput and low latency.\n\n - Stay up-to-date with advancements in machine learning and deep learning, and apply state-of-the-art techniques to enhance our solutions.\n\n - Evaluate trade-offs between different approaches, clearly articulate design choices, and develop detailed proposals for implementing new features.\n\n - Uncover, scope, and prioritize significant areas of technical debt across the software stack to ensure continued high quality of the inference service.\n\n - Build and maintain robust automated test suites to ensure software quality, performance, and reliability.\n\n - Contribute to an agile team environment by delivering high-quality software and adhering to agile development practices.\n\n - Lead cross-functional initiatives across the company to deliver high-quality inference solutions.\n\nSkills & Qualifications\n\n - Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Mathematics, or a related field.\n\n - 8+ years of experience in large-scale software engineering, with a focus on deep learning or related domains.\n\n - Proficiency in Python for building and maintaining scalable systems.\n\n - Advanced proficiency in C++, with an emphasis on multi-threaded programming, performance optimization, and system-level development.\n\n - Demonstrated experience driving cross-functional projects.\n\n - Experience building and scaling large-scale inference systems for LLMs or multimodal models.\n\n - Familiarity with LLM serving frameworks, such as vLLM, SGLang, and TensorRT-LLM.\n\n - Solid understanding of software architectural patterns for large-scale, high-performance applications.\n\n - Hands-on experience with ML frameworks, such as PyTorch, and a strong understanding of their underlying architectures.\n\n - Strong problem-solving skills, with the ability to balance technical depth with practical implementation constraints.\n\n - Exceptional communication and presentation skills, with the ability to work both independently and collaboratively across multidisciplinary teams.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"7fe218a3-7b69-4491-9042-a178fc304659","title":"Systems Engineering Technician","department":"Hardware Departments","team":"Systems","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-06-30T16:49:31.150+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/7fe218a3-7b69-4491-9042-a178fc304659","applyUrl":"https://jobs.ashbyhq.com/cerebras/7fe218a3-7b69-4491-9042-a178fc304659/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Position Summary
The Senior Systems Engineering Technician plays a critical role in building, testing, and troubleshooting complex mechanical and electrical systems in a fast-paced environment. This role requires a highly skilled, self-directed technician capable of working with minimal supervision, interpreting incomplete documentation, and driving hands-on solutions across multidisciplinary systems—including mechanical assemblies, electrical subsystems, and water-cooled components.
You will be a key contributor to prototype builds, system diagnostics, and iterative testing, partnering closely with engineers to bring advanced hardware concepts into reality.
Key Responsibilities
Mechanical Assembly & Integration — Build, assemble, and align complex mechanical systems consisting of large and small components, precision hardware, and multistage assemblies.
Electrical Testing & Troubleshooting — Perform electrical diagnostics, continuity checks, power testing, and root-cause analysis on wiring, PCBs, sensors, and control systems.
Water-Cooled System Support — Install, test, and maintain water-cooled subsystems, including pumps, manifolds, flow sensors, and leak-detection components.
Prototype & Lab Operations — Execute hands-on work in a lab environment with minimal direction, often using incomplete drawings or evolving engineering inputs.
Instrumentation & Data Collection — Set up test equipment, log performance data, and provide clear feedback to engineering teams.
Documentation & Process Improvement — Create or refine build instructions, test procedures, and troubleshooting guides. Open issue tickets with clear observations, supporting data, and recommended next steps.
Cross-Functional Collaboration — Work closely with mechanical, electrical, and systems engineers to validate designs, identify issues, and propose practical solutions.
Safety & Compliance — Maintain safe working practices around high-voltage systems, rotating equipment, pressure systems, and thermal management hardware.
Required Qualifications
5+ years of hands-on experience as an engineering technician in mechanical, electrical, or multidisciplinary hardware environments.
Proven ability to work independently with minimal supervision in a dynamic R&D or prototype lab setting.
Strong proficiency in mechanical assembly, including torquing, alignment, precision fitting, and interpreting mechanical drawings.
Demonstrated experience with electrical testing, troubleshooting, and safe handling of energized systems.
Experience working with water-cooled or fluid-cooled systems, including installation, leak testing, and flow verification.
Ability to read and interpret schematics, wiring diagrams, mechanical drawings, and test procedures.
Skilled with lab tools such as multimeters, oscilloscopes, torque tools, calipers, flow meters, and data-logging equipment.
Excellent communication skills and the ability to provide clear, actionable feedback to engineering teams.
Strong problem-solving mindset with the ability to diagnose ambiguous issues across mechanical and electrical domains.
Preferred Qualifications
Experience supporting prototype hardware, early-stage product development, or research environments.
Experience with thermal systems, heat exchangers, or coolant loop design.
Ability to create or update work instructions, test plans, and build documentation.
Comfort working with large assemblies, tight tolerances, and high-precision components.
Associate degree, technical certification, or equivalent hands-on experience.
Why This Role Matters
This position is ideal for a technician who thrives on autonomy, complexity, and hands-on engineering challenges. You’ll be a key contributor in transforming engineering concepts into functional, testable hardware—often serving as the first person to assemble, test, or operate new systems.
The base salary range for this position is $180,000 to $240,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nPosition Summary\n\nThe Senior Systems Engineering Technician plays a critical role in building, testing, and troubleshooting complex mechanical and electrical systems in a fast-paced environment. This role requires a highly skilled, self-directed technician capable of working with minimal supervision, interpreting incomplete documentation, and driving hands-on solutions across multidisciplinary systems—including mechanical assemblies, electrical subsystems, and water-cooled components.\n\nYou will be a key contributor to prototype builds, system diagnostics, and iterative testing, partnering closely with engineers to bring advanced hardware concepts into reality.\n\nKey Responsibilities\n\n - Mechanical Assembly & Integration — Build, assemble, and align complex mechanical systems consisting of large and small components, precision hardware, and multistage assemblies.\n\n - Electrical Testing & Troubleshooting — Perform electrical diagnostics, continuity checks, power testing, and root-cause analysis on wiring, PCBs, sensors, and control systems.\n\n - Water-Cooled System Support — Install, test, and maintain water-cooled subsystems, including pumps, manifolds, flow sensors, and leak-detection components.\n\n - Prototype & Lab Operations — Execute hands-on work in a lab environment with minimal direction, often using incomplete drawings or evolving engineering inputs.\n\n - Instrumentation & Data Collection — Set up test equipment, log performance data, and provide clear feedback to engineering teams.\n\n - Documentation & Process Improvement — Create or refine build instructions, test procedures, and troubleshooting guides. Open issue tickets with clear observations, supporting data, and recommended next steps.\n\n - Cross-Functional Collaboration — Work closely with mechanical, electrical, and systems engineers to validate designs, identify issues, and propose practical solutions.\n\n - Safety & Compliance — Maintain safe working practices around high-voltage systems, rotating equipment, pressure systems, and thermal management hardware.\n\nRequired Qualifications\n\n - 5+ years of hands-on experience as an engineering technician in mechanical, electrical, or multidisciplinary hardware environments.\n\n - Proven ability to work independently with minimal supervision in a dynamic R&D or prototype lab setting.\n\n - Strong proficiency in mechanical assembly, including torquing, alignment, precision fitting, and interpreting mechanical drawings.\n\n - Demonstrated experience with electrical testing, troubleshooting, and safe handling of energized systems.\n\n - Experience working with water-cooled or fluid-cooled systems, including installation, leak testing, and flow verification.\n\n - Ability to read and interpret schematics, wiring diagrams, mechanical drawings, and test procedures.\n\n - Skilled with lab tools such as multimeters, oscilloscopes, torque tools, calipers, flow meters, and data-logging equipment.\n\n - Excellent communication skills and the ability to provide clear, actionable feedback to engineering teams.\n\n - Strong problem-solving mindset with the ability to diagnose ambiguous issues across mechanical and electrical domains.\n\nPreferred Qualifications\n\n - Experience supporting prototype hardware, early-stage product development, or research environments.\n\n - Experience with thermal systems, heat exchangers, or coolant loop design.\n\n - Ability to create or update work instructions, test plans, and build documentation.\n\n - Comfort working with large assemblies, tight tolerances, and high-precision components.\n\n - Associate degree, technical certification, or equivalent hands-on experience.\n\nWhy This Role Matters\n\nThis position is ideal for a technician who thrives on autonomy, complexity, and hands-on engineering challenges. You’ll be a key contributor in transforming engineering concepts into functional, testable hardware—often serving as the first person to assemble, test, or operate new systems.\n\nThe base salary range for this position is $180,000 to $240,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"80775253-7fba-4a3b-87ee-0e70ce8e995c","title":"Software Engineer, Inference Platform ","department":"Software","team":"Cloud","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[{"location":"Toronto Office","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-06-20T01:28:09.918+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/80775253-7fba-4a3b-87ee-0e70ce8e995c","applyUrl":"https://jobs.ashbyhq.com/cerebras/80775253-7fba-4a3b-87ee-0e70ce8e995c/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We're hiring a Software Engineer to help contribute to projects on our Inference Platform team. Our team primarily owns the orchestration layer that runs inference on our datacenter clusters, connecting cloud components with machine learning services. We are often the first team to face problems that haven't been solved yet, leading solutions across Kubernetes operators, service security policies, and CI/CD.
If you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.
Responsibilities
Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.
Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.
Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.
Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.
Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.
Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.
Skills & Qualifications
3+ years of experience in software engineering, with experience building and operating large-scale distributed systems or cloud infrastructure.
Experience in distributed systems, ideally with Kubernetes.
Experience building highly available, latency-sensitive systems at scale.
Experience with security (certificates, TLS, mTLS).
Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.
Strong proficiency in backend or systems languages such as Go or C++.
Preferred Skills & Qualifications
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.
Location: Open to Sunnyvale or Toronto.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe're hiring a Software Engineer to help contribute to projects on our Inference Platform team. Our team primarily owns the orchestration layer that runs inference on our datacenter clusters, connecting cloud components with machine learning services. We are often the first team to face problems that haven't been solved yet, leading solutions across Kubernetes operators, service security policies, and CI/CD.\n\nIf you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.\n\nResponsibilities\n\n - Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.\n\n - Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.\n\n - Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.\n\n - Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.\n\n - Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.\n\n - Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.\n\nSkills & Qualifications\n\n - 3+ years of experience in software engineering, with experience building and operating large-scale distributed systems or cloud infrastructure.\n\n - Experience in distributed systems, ideally with Kubernetes.\n\n - Experience building highly available, latency-sensitive systems at scale.\n\n - Experience with security (certificates, TLS, mTLS).\n\n - Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.\n\n - Strong proficiency in backend or systems languages such as Go or C++.\n\nPreferred Skills & Qualifications\n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.\n\nLocation: Open to Sunnyvale or Toronto.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"83edf746-1972-4985-8ef1-a6dd50e4ddae","title":"Design Verification Engineer","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-06-04T18:36:28.794+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/83edf746-1972-4985-8ef1-a6dd50e4ddae","applyUrl":"https://jobs.ashbyhq.com/cerebras/83edf746-1972-4985-8ef1-a6dd50e4ddae/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Key Responsibilities
Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works for silicon.
Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.
Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.
Implement tests, manage regressions, gather coverage, and debug test failures.
Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.
Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.
Continuously enhances verification infrastructure and flows to improve efficiency and quality.
Contribute to the evolution of the overall verification methodology and best practices across the organization.
Skills and Qualifications
Great debugging and problem-solving skills.
Deep knowledge of SystemVerilog testbench, DPI and UVM.
Excellent programming skills and knowledge of software engineering practices including object-oriented design.
Experience developing scalable and portable testbenches and components.
Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.
Proficient in scripting languages such as Python or Perl.
Good interpersonal skills and the ability to work as a standout colleague are a must.
Extremely self-motivated and eager to solve problems
3+ years of Design Verification experience.
Desired Skills and Qualifications
Knowledge of pipelined processor architecture.
BS or MS in Computer Science or Electrical Engineering.
3+ years of hands-on Design Verification experience.
Location: India
The base salary range for this position is INR (80,00,000 – 1,10,00,000) annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nKey Responsibilities\n\n - Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works for silicon.\n\n - Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.\n\n - Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.\n\n - Implement tests, manage regressions, gather coverage, and debug test failures.\n\n - Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.\n\n - Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.\n\n - Continuously enhances verification infrastructure and flows to improve efficiency and quality.\n\n - Contribute to the evolution of the overall verification methodology and best practices across the organization.\n\nSkills and Qualifications\n\n - Great debugging and problem-solving skills.\n\n - Deep knowledge of SystemVerilog testbench, DPI and UVM.\n\n - Excellent programming skills and knowledge of software engineering practices including object-oriented design.\n\n - Experience developing scalable and portable testbenches and components.\n\n - Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.\n\n - Proficient in scripting languages such as Python or Perl.\n\n - Good interpersonal skills and the ability to work as a standout colleague are a must.\n\n - Extremely self-motivated and eager to solve problems\n\n - 3+ years of Design Verification experience.\n\nDesired Skills and Qualifications\n\n - Knowledge of pipelined processor architecture.\n\n - BS or MS in Computer Science or Electrical Engineering.\n\n - 3+ years of hands-on Design Verification experience.\n\nLocation: India\n\nThe base salary range for this position is INR (80,00,000 – 1,10,00,000) annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"84a9df6b-fe96-4711-8106-971d829b6dc2","title":"Network Security Engineer","department":"Security Department","team":"Security & IT","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-06-23T17:31:31.364+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/84a9df6b-fe96-4711-8106-971d829b6dc2","applyUrl":"https://jobs.ashbyhq.com/cerebras/84a9df6b-fe96-4711-8106-971d829b6dc2/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking a Network Security Engineer to design, build, and operate the network security controls that keep Cerebras's data centers, cloud environments, and corporate infrastructure secure as we scale to support the world's most demanding AI workloads. You will own the lifecycle of our firewall, segmentation, and network detection capabilities — turning policy into automated, testable infrastructure — and partner closely with Network Engineering, IT, and Security Operations to keep the environment safe and operational. The right candidate brings hands-on network security depth, an automation-first mindset, and the ability to operate across enterprise, data center, and cloud network domains.
Responsibilities
Design and operate firewall, segmentation, and zero-trust controls across data center, corporate, and cloud (AWS) networks.
Build and maintain network security infrastructure as code — including firewall rules, policy automation, and CI/CD-driven deployment.
Lead network lifecycle management: design review, configuration baselines, change automation, and ongoing rule hygiene.
Build detection capabilities for network-based attacker behaviors and partner with the Detection & Response team on response playbooks.
Implement and operate network access controls including ZTNA, VPN, and remote access patterns.
Drive periodic firewall rule reviews, segmentation audits, and remediation campaigns to reduce risk and complexity.
Document network security architecture, controls, and operating procedures in clear runbooks.
Skills and Qualifications
Master's degree or higher in computer science.
Deep expertise with industry leading firewalls, including policy design, automation, and operations.
Strong proficiency with infrastructure as code (Terraform, Ansible) and at least one scripting language (Python preferred).
Hands-on experience operating network controls in a major cloud environment (AWS preferred), including VPCs, transit gateways, security groups, and cloud-native firewalls.
Practical understanding of ZTNA, segmentation, and modern network access patterns.
Solid fundamentals in TCP/IP, routing, switching, DNS, and TLS — with the ability to troubleshoot across the stack.
Excellent written communication skills, with the ability to create clear documentation for both engineers and operators.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\nWe are seeking a Network Security Engineer to design, build, and operate the network security controls that keep Cerebras's data centers, cloud environments, and corporate infrastructure secure as we scale to support the world's most demanding AI workloads. You will own the lifecycle of our firewall, segmentation, and network detection capabilities — turning policy into automated, testable infrastructure — and partner closely with Network Engineering, IT, and Security Operations to keep the environment safe and operational. The right candidate brings hands-on network security depth, an automation-first mindset, and the ability to operate across enterprise, data center, and cloud network domains.\n\nResponsibilities\n\n - Design and operate firewall, segmentation, and zero-trust controls across data center, corporate, and cloud (AWS) networks.\n\n - Build and maintain network security infrastructure as code — including firewall rules, policy automation, and CI/CD-driven deployment.\n\n - Lead network lifecycle management: design review, configuration baselines, change automation, and ongoing rule hygiene.\n\n - Build detection capabilities for network-based attacker behaviors and partner with the Detection & Response team on response playbooks.\n\n - Implement and operate network access controls including ZTNA, VPN, and remote access patterns.\n\n - Drive periodic firewall rule reviews, segmentation audits, and remediation campaigns to reduce risk and complexity.\n\n - Document network security architecture, controls, and operating procedures in clear runbooks.\n\nSkills and Qualifications\n\n - Master's degree or higher in computer science.\n\n - Deep expertise with industry leading firewalls, including policy design, automation, and operations.\n\n - Strong proficiency with infrastructure as code (Terraform, Ansible) and at least one scripting language (Python preferred).\n\n - Hands-on experience operating network controls in a major cloud environment (AWS preferred), including VPCs, transit gateways, security groups, and cloud-native firewalls.\n\n - Practical understanding of ZTNA, segmentation, and modern network access patterns.\n\n - Solid fundamentals in TCP/IP, routing, switching, DNS, and TLS — with the ability to troubleshoot across the stack.\n\n - Excellent written communication skills, with the ability to create clear documentation for both engineers and operators.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"864698cd-da36-42b6-bbcc-fc39d22010f0","title":"AI Engineer, Model Quality and Performance","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-05-15T12:28:49.572+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/864698cd-da36-42b6-bbcc-fc39d22010f0","applyUrl":"https://jobs.ashbyhq.com/cerebras/864698cd-da36-42b6-bbcc-fc39d22010f0/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
You'll own model quality and performance for Cerebras' inference offerings. You will define what \"good\" looks like across the models we serve, building AI-driven systems to measure it at scale, and translating those signals into artifacts our customers and product team actually use.
You'll use AI agents to spin up custom eval suites per customer use case, mine trajectories for representative test data, automate the repetitive parts of release qual, and help build performance datasets and benchmarking workflows for customer use cases. We want someone whose first instinct is \"how do I get an AI agent to do this on a loop.\"
You'll sit between engineering, product, and customer-facing teams.
What You'll Do
Design eval suites with AI agents in the loop. For every model release, curate a thoughtful mix of advanced, basic, long-context, and customer-use-case-specific evals. Use Claude to generate, validate, and prune candidate test cases at speed.
Build custom evals for target customers by orchestrating AI agents to mine trajectories from their workloads and synthesize representative eval sets.
Automate eval execution end-to-end with AI-driven pipelines on top of standard tooling (Docker, Git, CI). The goal is a system that runs itself between releases, not a script you re-run by hand.
Build automations to forecast and benchmark model performance on Cerebras for our top customers, including modeling how fast customer-specific workloads will run in production.
Build product-quality tooling that synthesizes quality + performance data into a single, easy-to-use view.
Experience building AI agents. You ship real systems with Claude (or equivalent) as a force multiplier. You've built things that would have been infeasible solo without AI agents in the loop.
Strong math/stats background..
Comfort with Docker, Git, and the standard automation stack
A taste for tooling design. You've shipped something that a non-engineer used without complaining. Bonus if AI helped you ship it.
Performance-tuning experience on custom silicon, GPUs, or FPGAs.
Experience designing evals for agentic / coding / long-context / multimodal use cases.
Familiarity with open-source eval frameworks (EvalScope, lm-eval-harness, etc.).
Experience building AI agents.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nYou'll own model quality and performance for Cerebras' inference offerings. You will define what \"good\" looks like across the models we serve, building AI-driven systems to measure it at scale, and translating those signals into artifacts our customers and product team actually use.\n\nYou'll use AI agents to spin up custom eval suites per customer use case, mine trajectories for representative test data, automate the repetitive parts of release qual, and help build performance datasets and benchmarking workflows for customer use cases. We want someone whose first instinct is \"how do I get an AI agent to do this on a loop.\"\n\nYou'll sit between engineering, product, and customer-facing teams. \n\nWhat You'll Do\n\n - Design eval suites with AI agents in the loop. For every model release, curate a thoughtful mix of advanced, basic, long-context, and customer-use-case-specific evals. Use Claude to generate, validate, and prune candidate test cases at speed.\n\n - Build custom evals for target customers by orchestrating AI agents to mine trajectories from their workloads and synthesize representative eval sets.\n\n - Automate eval execution end-to-end with AI-driven pipelines on top of standard tooling (Docker, Git, CI). The goal is a system that runs itself between releases, not a script you re-run by hand.\n\n - Build automations to forecast and benchmark model performance on Cerebras for our top customers, including modeling how fast customer-specific workloads will run in production.\n\n - Build product-quality tooling that synthesizes quality + performance data into a single, easy-to-use view. \n\n\nSKILLS & QUALIFICATIONS\n\n - Experience building AI agents. You ship real systems with Claude (or equivalent) as a force multiplier. You've built things that would have been infeasible solo without AI agents in the loop.\n\n - Strong math/stats background..\n\n - Comfort with Docker, Git, and the standard automation stack\n\n - A taste for tooling design. You've shipped something that a non-engineer used without complaining. Bonus if AI helped you ship it.\n\n\nASSETS\n\n - Performance-tuning experience on custom silicon, GPUs, or FPGAs. \n\n - Experience designing evals for agentic / coding / long-context / multimodal use cases.\n\n - Familiarity with open-source eval frameworks (EvalScope, lm-eval-harness, etc.).\n\n - Experience building AI agents.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"87943434-237a-4649-817e-2dcc20347a23","title":"Infrastructure Hardware Technical Program Manager (Server and Network Systems)","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-02-19T14:10:15.133+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/87943434-237a-4649-817e-2dcc20347a23","applyUrl":"https://jobs.ashbyhq.com/cerebras/87943434-237a-4649-817e-2dcc20347a23/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As an Infrastructure Hardware Technical Program Manager (Server and Network Systems) on the Cluster Architecture Team, you will drive end-to-end delivery of server and network platform programs across Cerebras CS-3–based AI clusters — from requirements and vendor selection through lab bring-up, qualification, and production rollout. You will be the execution owner for multi-team programs spanning OEM/ODM partners, component vendors, internal software/runtime teams and architects, validation/QA, and deployment/operations.
About This Role
This role is intentionally technical: you must understand server, network, and system-level trade-offs well enough to run effective technical reviews, keep programs grounded in real constraints, and maintain a crisp decision trail - while partnering closely with the Compute / Server / Network Platform Architects for detailed technical direction and sign-off. You will also build shared understanding with our rack/elevations and physical datacenter design partners so that server and network changes land smoothly in real deployments (without owning physical DC design).
Responsibilities
Own end-to-end program execution for server systems and network equipment in Cerebras clusters, including new platforms, refreshes, and major component/config changes.
Drive requirements gathering and convert inputs into executable plans with clear milestones, readiness gates, and cross-functional deliverables.
Represent Cluster Architecture in executive reviews, OKR cycles, and leadership/customer forums as needed.
Build and manage integrated schedules across vendors and internal teams, track dependencies, critical path, and risks.
Manage OEM/ODM and switch/vendor engagements (RFI/RFP, samples, escalations, roadmap alignment).
Partner with Compute / Server Platform / Network Architects to turn architectural decisions into qualification plans, acceptance criteria, and rollout strategies.
Lead qualification and release readiness (lab/staging validation, regression tracking, go/no-go decisions).
Own risk and change management into production, including versioning, rollout sequencing, and stakeholder communication.
Ensure operational readiness with deployment and fleet teams and maintain alignment with rack/physical DC owners on power, cooling, space, and cabling constraints.
Skills and Qualifications
B.S. or M.S. in Computer Science, Electrical/Computer Engineering, or equivalent experience.
8+ years in Technical Program Management (or similar delivery leadership) for server, network, or infrastructure platforms from concept through production.
Experience coordinating complex server and/or datacenter network programs across OEM/ODMs, switch vendors, and internal engineering teams.
Working knowledge of server architecture (CPU/NUMA, memory bandwidth, PCIe, NIC and storage IO) and enough networking fundamentals (leaf-spine fabrics, switch platforms, high-performance interconnects) to run effective technical reviews.
Familiarity with Linux server fleet management (provisioning, firmware/BIOS, drivers, field triage).
Strong multi-team program execution skills: integrated plans, risk management, dependency tracking, and executive-level communication.
Ability to operate in ambiguity and keep parallel server and network workstreams aligned.
Experience with AI/ML, HPC, or performance-sensitive distributed infrastructure is a plus.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAs an Infrastructure Hardware Technical Program Manager (Server and Network Systems) on the Cluster Architecture Team, you will drive end-to-end delivery of server and network platform programs across Cerebras CS-3–based AI clusters — from requirements and vendor selection through lab bring-up, qualification, and production rollout. You will be the execution owner for multi-team programs spanning OEM/ODM partners, component vendors, internal software/runtime teams and architects, validation/QA, and deployment/operations.\n\nAbout This Role\n\nThis role is intentionally technical: you must understand server, network, and system-level trade-offs well enough to run effective technical reviews, keep programs grounded in real constraints, and maintain a crisp decision trail - while partnering closely with the Compute / Server / Network Platform Architects for detailed technical direction and sign-off. You will also build shared understanding with our rack/elevations and physical datacenter design partners so that server and network changes land smoothly in real deployments (without owning physical DC design).\n\nResponsibilities\n\n - Own end-to-end program execution for server systems and network equipment in Cerebras clusters, including new platforms, refreshes, and major component/config changes.\n\n - Drive requirements gathering and convert inputs into executable plans with clear milestones, readiness gates, and cross-functional deliverables.\n\n - Represent Cluster Architecture in executive reviews, OKR cycles, and leadership/customer forums as needed.\n\n - Build and manage integrated schedules across vendors and internal teams, track dependencies, critical path, and risks.\n\n - Manage OEM/ODM and switch/vendor engagements (RFI/RFP, samples, escalations, roadmap alignment).\n\n - Partner with Compute / Server Platform / Network Architects to turn architectural decisions into qualification plans, acceptance criteria, and rollout strategies.\n\n - Lead qualification and release readiness (lab/staging validation, regression tracking, go/no-go decisions).\n\n - Own risk and change management into production, including versioning, rollout sequencing, and stakeholder communication.\n\n - Ensure operational readiness with deployment and fleet teams and maintain alignment with rack/physical DC owners on power, cooling, space, and cabling constraints.\n\n Skills and Qualifications\n\n - B.S. or M.S. in Computer Science, Electrical/Computer Engineering, or equivalent experience.\n\n - 8+ years in Technical Program Management (or similar delivery leadership) for server, network, or infrastructure platforms from concept through production.\n\n - Experience coordinating complex server and/or datacenter network programs across OEM/ODMs, switch vendors, and internal engineering teams.\n\n - Working knowledge of server architecture (CPU/NUMA, memory bandwidth, PCIe, NIC and storage IO) and enough networking fundamentals (leaf-spine fabrics, switch platforms, high-performance interconnects) to run effective technical reviews.\n\n - Familiarity with Linux server fleet management (provisioning, firmware/BIOS, drivers, field triage).\n\n - Strong multi-team program execution skills: integrated plans, risk management, dependency tracking, and executive-level communication.\n\n - Ability to operate in ambiguity and keep parallel server and network workstreams aligned.\n\n - Experience with AI/ML, HPC, or performance-sensitive distributed infrastructure is a plus.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"8b729a93-04bd-49da-8e87-5eb4ff3c8a26","title":"Principal Network Security Architect","department":"Security Department","team":"Security & IT","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-06-23T17:35:45.489+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/8b729a93-04bd-49da-8e87-5eb4ff3c8a26","applyUrl":"https://jobs.ashbyhq.com/cerebras/8b729a93-04bd-49da-8e87-5eb4ff3c8a26/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking a Principal Network Security Architect to lead the design and evolution of the networks that connect Cerebras's data centers, offices, and cloud environments — the foundation that delivers the fastest AI inference on earth to customers like OpenAI and AWS. You will set the architectural direction for high-performance, resilient enterprise and data center networking, and partner closely with Site Reliability, Security, and Infrastructure to operate at the scale and speed our compute demands. The right candidate brings senior network design depth, a track record of building at hyperscale, and the judgment to balance performance, reliability, and security in a rapidly growing environment.
Responsibilities
Define and own the architectural roadmap for Cerebras's enterprise, data center, and cloud network estate.
Co-author secure design and lifecycle management of high-performance data center networking — including spine/leaf, RDMA, and high-bandwidth fabrics supporting wafer-scale compute.
Build and maintain an AI-agent based analysis and review framework for network changes as well as self-improvement driven by observed network patterns and use cases.
Partner with Network Security to deliver segmented, zero-trust-aligned network designs across data center and corporate environments.
Set standards for resiliency, observability, and capacity planning across the global network
Mentor engineers across regions (US, Canada, Bangalore, and beyond), and serve as the senior technical voice on cross-functional network initiatives.
Stay ahead of emerging networking patterns relevant to AI infrastructure and translate them into actionable architecture decisions.
Skills and Qualifications
10+ years of experience in enterprise and/or data center network engineering, including hands-on design and operations at scale.
Deep understanding in cloud networking and service mesh, with emphasis on K8s service mesh and virtual networks.
Deep expertise in routing, switching, and data center fabrics — including BGP, EVPN/VXLAN, and high-bandwidth/low-latency designs.
Hands-on experience with networking for high-performance compute or AI/ML workloads (RDMA, RoCE, InfiniBand exposure a plus).
Strong proficiency with network automation — infrastructure as code (Ansible, Terraform), version-controlled configuration, and CI/CD for network change.
Working knowledge of cloud networking (AWS preferred), including VPCs, transit gateways, Direct Connect, and hybrid connectivity patterns.
Experience operating networks at multi-site, global scale — including capacity planning, incident response, and vendor management.
Excellent written and verbal communication skills, with the ability to lead architecture conversations across technical and non-technical audiences.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nWe are seeking a Principal Network Security Architect to lead the design and evolution of the networks that connect Cerebras's data centers, offices, and cloud environments — the foundation that delivers the fastest AI inference on earth to customers like OpenAI and AWS. You will set the architectural direction for high-performance, resilient enterprise and data center networking, and partner closely with Site Reliability, Security, and Infrastructure to operate at the scale and speed our compute demands. The right candidate brings senior network design depth, a track record of building at hyperscale, and the judgment to balance performance, reliability, and security in a rapidly growing environment.\n\nResponsibilities\n\n - Define and own the architectural roadmap for Cerebras's enterprise, data center, and cloud network estate.\n\n - Co-author secure design and lifecycle management of high-performance data center networking — including spine/leaf, RDMA, and high-bandwidth fabrics supporting wafer-scale compute.\n\n - Build and maintain an AI-agent based analysis and review framework for network changes as well as self-improvement driven by observed network patterns and use cases.\n\n - Partner with Network Security to deliver segmented, zero-trust-aligned network designs across data center and corporate environments.\n\n - Set standards for resiliency, observability, and capacity planning across the global network\n\n - Mentor engineers across regions (US, Canada, Bangalore, and beyond), and serve as the senior technical voice on cross-functional network initiatives.\n\n - Stay ahead of emerging networking patterns relevant to AI infrastructure and translate them into actionable architecture decisions.\n\nSkills and Qualifications\n\n - 10+ years of experience in enterprise and/or data center network engineering, including hands-on design and operations at scale.\n\n - Deep understanding in cloud networking and service mesh, with emphasis on K8s service mesh and virtual networks.\n\n - Deep expertise in routing, switching, and data center fabrics — including BGP, EVPN/VXLAN, and high-bandwidth/low-latency designs.\n\n - Hands-on experience with networking for high-performance compute or AI/ML workloads (RDMA, RoCE, InfiniBand exposure a plus).\n\n - Strong proficiency with network automation — infrastructure as code (Ansible, Terraform), version-controlled configuration, and CI/CD for network change.\n\n - Working knowledge of cloud networking (AWS preferred), including VPCs, transit gateways, Direct Connect, and hybrid connectivity patterns.\n\n - Experience operating networks at multi-site, global scale — including capacity planning, incident response, and vendor management.\n\n - Excellent written and verbal communication skills, with the ability to lead architecture conversations across technical and non-technical audiences.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"8f7c4fa6-cb09-460c-98e1-d9f4f7928f28","title":"Product Manager, Strategic Verticals ","department":"Product Management Departments","team":"Product Management","employmentType":"FullTime","location":"San Francisco ","secondaryLocations":[],"publishedAt":"2025-09-23T14:30:39.813+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/8f7c4fa6-cb09-460c-98e1-d9f4f7928f28","applyUrl":"https://jobs.ashbyhq.com/cerebras/8f7c4fa6-cb09-460c-98e1-d9f4f7928f28/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Our customers span leading AI Native companies, Fortune 500 Enterprises, Sovereign AI and Federal programs, and leading research institutions. Our mission is to deliver the platform that unlocks the next generation of AI applications, providing the fundamentally new capability to leverage the most intelligent models at real-time serving speeds.
Why Cerebras?
Here at Cerebras, we have built the world’s first wafer-scale compute platform and software stack, purpose-designed to accelerate generative AI by over 10-20x what is possible on legacy processors today. AI developers are limited today by the constant tradeoffs between model quality, speed, and cost, and Cerebras’ mission is to remove these limitations to unlock AI creativity and potential.
Unmatched speed. Our third-generation Wafer-Scale Engine (WSE-3) delivers sub-ms inference latencies and training throughput that eclipses GPU clusters by over 10x. Think instant code generation, instant design creation, agents that interact seamlessly and responsively to their users and environment.
Full-stack innovation. From custom silicon to compilers, model research, and turnkey cloud inference, we are innovating and integrating at every layer so customers can focus on breakthroughs, not bottlenecks.
Real-world impact. Cerebras customers are transforming industries across healthcare, energy, science, government, startup ecosystems, and more. We’re proud to be serving customers spanning the Fortune 500, government labs, and AI-native unicorns.
Backed to win. Cerebras is supported by top investors, like Benchmark, Altimeter, Eclipse, and Coatue.
Fearless and fun culture. We’re a close-knit, creative team that tackles all challenges with optimism and collaboration. We’ve already productized the world’s largest chip by over 50x. How hard can the next problem be? :)
About The Role
As a founding member of the Strategic Verticals product team at Cerebras, you are the tip of the spear for our company. You’ll embed with our most strategic customers, from AI-native startups shipping 0-to-1 products to Fortune 500 enterprises transforming their industries, to translate and guide their ambitions into blazing-fast, production-ready AI solutions.
Think of yourself as part product leader, part technical expert, and part GTM strategist:
Own the outcome – From first whiteboard session to scaled deployment, you are directly accountable for customer success, adoption, and expansion.
Design for speed – Craft PoCs that showcase Cerebras’ latency super-powers, advise on model selection / fine-tuning, and benchmark end-to-end performance.
Navigate complexities – pitch new ideas, align internal and customer stakeholders, unblock hurdles, and convert customer interest into long-term, thriving partnerships.
Shape the roadmap – Distill customer insights into structured product feedback requirements, influencing future software features and chip and cluster designs.
Successful candidates will be passionate about creative problem solving and idea generation, learning and embedding into new domains, building relationships, and delighting customers.
You’ll have the opportunity to learn about and enable some of the most impactful AI products in the world, with industry-leading organizations across each vertical. You will get to work closely with a tight-knit product team, in a fast-moving but supportive environment. Your scope and career here will be driven by your passion, ability, and impact – not by your seniority or prior experience.
Key Responsibilities
You will:
Be the product leader on our most critical lighthouse accounts, each pushing the limits of what’s possible with GenAI.
Engage directly with companies from AI Natives at the cutting edge to large enterprises transforming their industries, to deeply understand their needs, goals, and requirements.
Co-architect solutions— partner with Solutions Architects, Account Managers, and our Engineering and Product teams to design tailored solutions that leverage our 10x faster speed advatanges to transform customer applications.
Directly advise on customers’ long-term AI strategies
Become a go-to-market ninja. You will be co-owning the end-to-end customer journey, working across Sales, Solutions Architects, Marketing, Engineering, and Product teams to convert interest into long-term usage and expansion. As part of this, you will also be continuously helping to improve and optimize our processes.
Identify new collaboration opportunities and use cases within accounts to expand Cerebras’ partnership with them.
Drive the product roadmap, working closely with engineering, ML, and other product teams across the company to bring your deep understanding of customer requirements to drive future feature development.
Skills & Qualifications
Strong technical background (CS/EE background, or prior experience as a SWE), and familiarity with LLMs, inference needs, agents, etc.
5+ years of experience as a product manager or SWE, currently at or above the level of Senior PM or SWE. Ideally, on a developer-facing product.
Excellent ability to communicate with customers and navigate complex, high-stakes scenarios.
Ability to thrive in a fast-paced, dynamic environment.
Self-starter with an entrepreneurial sense of ownership of overall team and product success, and the ability to make things happen around you. A bias towards getting things done, owning the solution, and driving problems to resolution.
Deep passion for creative problem solving and customer success.
Preferred requirements
Experience with LLM serving stacks (vLLM, TensorRT-LLM, TGI), agent frameworks, etc.
Interest in developer platforms and tooling.
MBA of equivalent professional experience.
You’ll thrive in this role if you:
Are T-shaped
Take pride in habitual excellence
Love working with customers to drive impact and outcomes end-to-end
Are passionate about innovative technology and the potential of AI to transform how we live and work for the better
Are a former engineer who wants to have direct influence and impact on the business
Location
Hybrid at our Sunnyvale, CA office.
Remote possible for candidates willing to travel 1-2x per quarter.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nOur customers span leading AI Native companies, Fortune 500 Enterprises, Sovereign AI and Federal programs, and leading research institutions. Our mission is to deliver the platform that unlocks the next generation of AI applications, providing the fundamentally new capability to leverage the most intelligent models at real-time serving speeds. \n\nWhy Cerebras? \n\nHere at Cerebras, we have built the world’s first wafer-scale compute platform and software stack, purpose-designed to accelerate generative AI by over 10-20x what is possible on legacy processors today. AI developers are limited today by the constant tradeoffs between model quality, speed, and cost, and Cerebras’ mission is to remove these limitations to unlock AI creativity and potential. \n\n - Unmatched speed. Our third-generation Wafer-Scale Engine (WSE-3) delivers sub-ms inference latencies and training throughput that eclipses GPU clusters by over 10x. Think instant code generation, instant design creation, agents that interact seamlessly and responsively to their users and environment. \n\n - Full-stack innovation. From custom silicon to compilers, model research, and turnkey cloud inference, we are innovating and integrating at every layer so customers can focus on breakthroughs, not bottlenecks. \n\n - Real-world impact. Cerebras customers are transforming industries across healthcare, energy, science, government, startup ecosystems, and more. We’re proud to be serving customers spanning the Fortune 500, government labs, and AI-native unicorns. \n\n - Backed to win. Cerebras is supported by top investors, like Benchmark, Altimeter, Eclipse, and Coatue. \n\n - Fearless and fun culture. We’re a close-knit, creative team that tackles all challenges with optimism and collaboration. We’ve already productized the world’s largest chip by over 50x. How hard can the next problem be? :) \n\nAbout The Role \n\nAs a founding member of the Strategic Verticals product team at Cerebras, you are the tip of the spear for our company. You’ll embed with our most strategic customers, from AI-native startups shipping 0-to-1 products to Fortune 500 enterprises transforming their industries, to translate and guide their ambitions into blazing-fast, production-ready AI solutions. \n\nThink of yourself as part product leader, part technical expert, and part GTM strategist: \n\n 1. Own the outcome – From first whiteboard session to scaled deployment, you are directly accountable for customer success, adoption, and expansion. \n\n 2. Design for speed – Craft PoCs that showcase Cerebras’ latency super-powers, advise on model selection / fine-tuning, and benchmark end-to-end performance. \n\n 3. Navigate complexities – pitch new ideas, align internal and customer stakeholders, unblock hurdles, and convert customer interest into long-term, thriving partnerships. \n\n 4. Shape the roadmap – Distill customer insights into structured product feedback requirements, influencing future software features and chip and cluster designs. \n\nSuccessful candidates will be passionate about creative problem solving and idea generation, learning and embedding into new domains, building relationships, and delighting customers. \n\nYou’ll have the opportunity to learn about and enable some of the most impactful AI products in the world, with industry-leading organizations across each vertical. You will get to work closely with a tight-knit product team, in a fast-moving but supportive environment. Your scope and career here will be driven by your passion, ability, and impact – not by your seniority or prior experience. \n\nKey Responsibilities \n\nYou will: \n\n - Be the product leader on our most critical lighthouse accounts, each pushing the limits of what’s possible with GenAI. \n\n - Engage directly with companies from AI Natives at the cutting edge to large enterprises transforming their industries, to deeply understand their needs, goals, and requirements. \n\n - Co-architect solutions— partner with Solutions Architects, Account Managers, and our Engineering and Product teams to design tailored solutions that leverage our 10x faster speed advatanges to transform customer applications. \n\n - Directly advise on customers’ long-term AI strategies \n\n - Become a go-to-market ninja. You will be co-owning the end-to-end customer journey, working across Sales, Solutions Architects, Marketing, Engineering, and Product teams to convert interest into long-term usage and expansion. As part of this, you will also be continuously helping to improve and optimize our processes. \n\n - Identify new collaboration opportunities and use cases within accounts to expand Cerebras’ partnership with them. \n\n - Drive the product roadmap, working closely with engineering, ML, and other product teams across the company to bring your deep understanding of customer requirements to drive future feature development. \n\nSkills & Qualifications \n\n - Strong technical background (CS/EE background, or prior experience as a SWE), and familiarity with LLMs, inference needs, agents, etc. \n\n - 5+ years of experience as a product manager or SWE, currently at or above the level of Senior PM or SWE. Ideally, on a developer-facing product. \n\n - Excellent ability to communicate with customers and navigate complex, high-stakes scenarios. \n\n - Ability to thrive in a fast-paced, dynamic environment. \n\n - Self-starter with an entrepreneurial sense of ownership of overall team and product success, and the ability to make things happen around you. A bias towards getting things done, owning the solution, and driving problems to resolution. \n\n - Deep passion for creative problem solving and customer success. \n\nPreferred requirements \n\n - Experience with LLM serving stacks (vLLM, TensorRT-LLM, TGI), agent frameworks, etc. \n\n - Interest in developer platforms and tooling. \n\n - MBA of equivalent professional experience. \n\nYou’ll thrive in this role if you: \n\n - Are T-shaped \n\n - Take pride in habitual excellence \n\n - Love working with customers to drive impact and outcomes end-to-end \n\n - Are passionate about innovative technology and the potential of AI to transform how we live and work for the better \n\n - Are a former engineer who wants to have direct influence and impact on the business \n\nLocation \n\n - Hybrid at our Sunnyvale, CA office. \n\n - Remote possible for candidates willing to travel 1-2x per quarter. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"90879967-1071-4d05-9180-6e18023ed887","title":"Senior ML Software Engineer - Integration & Quality","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-02-05T16:10:29.592+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/90879967-1071-4d05-9180-6e18023ed887","applyUrl":"https://jobs.ashbyhq.com/cerebras/90879967-1071-4d05-9180-6e18023ed887/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are looking for a Software Engineer to join the ML Integration and Quality team at Cerebras. This team sits at the intersection of machine learning infrastructure, distributed systems, and hardware/software co-design.
In this role, you will help integrate and validate the software stack that powers the Cerebras AI platform, ensuring large-scale ML workloads run reliably and efficiently across our systems. You will work closely with engineers across runtime, compiler, kernel, and hardware teams to debug complex issues, improve automation, and strengthen the reliability of our AI infrastructure.
This is an excellent opportunity for engineers who enjoy working across the stack, debugging complex systems, and improving the reliability of large-scale AI platforms.
Responsibilities
Integrate and validate software components across the Cerebras AI platform.
Collaborate with engineers across ML runtime, compiler, kernel, and hardware teams to ensure reliable feature integration.
Investigate and debug complex issues across distributed systems and large-scale ML workloads.
Build automation tools and infrastructure to support integration testing, system validation, and debugging workflows.
Develop and maintain testbeds used to validate system performance and reliability.
Identify system bottlenecks, failure points, and edge cases that impact ML workload performance.
Contribute to test plans and validation strategies for new features and platform capabilities.
Improve observability, diagnostics, and debugging workflows across the ML software stack.
Work with product and engineering teams to ensure high-quality releases of the Cerebras inference platform.
Minimum Skills & Qualifications
~5 years of experience in software engineering, systems engineering, or infrastructure development.
Strong programming skills in Python, C++, Go, or similar languages.
Experience debugging complex systems or distributed software environments.
Familiarity with systems-level development, infrastructure tooling, or platform integration.
Experience building automation tools, testing frameworks, or internal developer tooling.
Strong problem-solving skills and the ability to investigate issues across multiple system layers.
Excellent communication and collaboration skills.
Preferred Skills
Experience working with machine learning infrastructure or ML model deployment.
Familiarity with LLM or multimodal model workloads.
Experience with distributed systems, cloud infrastructure, or large-scale compute clusters.
Exposure to performance debugging, profiling, or system observability tools.
Experience with microservices, containerized environments, or cluster orchestration.
Exposure to hardware accelerators, compilers, or ML frameworks.
This role follows a hybrid schedule, requiring in-office presence 3 days per Please note, fully remote is not an option.
Office locations: Sunnyvale, CA or Toronto, ON.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are looking for a Software Engineer to join the ML Integration and Quality team at Cerebras. This team sits at the intersection of machine learning infrastructure, distributed systems, and hardware/software co-design.\n\nIn this role, you will help integrate and validate the software stack that powers the Cerebras AI platform, ensuring large-scale ML workloads run reliably and efficiently across our systems. You will work closely with engineers across runtime, compiler, kernel, and hardware teams to debug complex issues, improve automation, and strengthen the reliability of our AI infrastructure.\n\nThis is an excellent opportunity for engineers who enjoy working across the stack, debugging complex systems, and improving the reliability of large-scale AI platforms.\n\nResponsibilities\n\n - Integrate and validate software components across the Cerebras AI platform.\n\n - Collaborate with engineers across ML runtime, compiler, kernel, and hardware teams to ensure reliable feature integration.\n\n - Investigate and debug complex issues across distributed systems and large-scale ML workloads.\n\n - Build automation tools and infrastructure to support integration testing, system validation, and debugging workflows.\n\n - Develop and maintain testbeds used to validate system performance and reliability.\n\n - Identify system bottlenecks, failure points, and edge cases that impact ML workload performance.\n\n - Contribute to test plans and validation strategies for new features and platform capabilities.\n\n - Improve observability, diagnostics, and debugging workflows across the ML software stack.\n\n - Work with product and engineering teams to ensure high-quality releases of the Cerebras inference platform.\n\nMinimum Skills & Qualifications\n\n - ~5 years of experience in software engineering, systems engineering, or infrastructure development.\n\n - Strong programming skills in Python, C++, Go, or similar languages.\n\n - Experience debugging complex systems or distributed software environments.\n\n - Familiarity with systems-level development, infrastructure tooling, or platform integration.\n\n - Experience building automation tools, testing frameworks, or internal developer tooling.\n\n - Strong problem-solving skills and the ability to investigate issues across multiple system layers.\n\n - Excellent communication and collaboration skills.\n\nPreferred Skills\n\n - Experience working with machine learning infrastructure or ML model deployment.\n\n - Familiarity with LLM or multimodal model workloads.\n\n - Experience with distributed systems, cloud infrastructure, or large-scale compute clusters.\n\n - Exposure to performance debugging, profiling, or system observability tools.\n\n - Experience with microservices, containerized environments, or cluster orchestration.\n\n - Exposure to hardware accelerators, compilers, or ML frameworks.\n\n\nLOCATION\n\n - This role follows a hybrid schedule, requiring in-office presence 3 days per Please note, fully remote is not an option.\n\n - Office locations: Sunnyvale, CA or Toronto, ON. \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"915ed244-bc69-48fb-bbc0-9347d2f32fa3","title":"Lead RTL Design Engineer","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2025-11-13T15:26:55.771+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/915ed244-bc69-48fb-bbc0-9347d2f32fa3","applyUrl":"https://jobs.ashbyhq.com/cerebras/915ed244-bc69-48fb-bbc0-9347d2f32fa3/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a lead front-end design engineer, you will be a key part of the world-class team designing and developing the next generations of the Cerebras Wafer Scale Engine (WSE).
This role requires deep expertise in RTL design and integration, with a strong focus on delivering high-performance, power-efficient, and scalable solutions. The role also requires close collaboration and management of external ASIC vendor. You will collaborate closely with the design verification, physical design, software and system teams to bring innovative semiconductor architectures from concept to production, addressing the unique challenges of building WSE systems.
Responsibilities
Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL development, Synthesis.
Managing external ASIC vendor through product development cycle.
Work closely with PD team members for design closure to meet PPA goals.
Work closely with Design verification and DFT teams for achieving the best functional and test coverage.
Work with software and system teams to understand opportunities to deliver optimal performance and feature set for the product.
Debug silicon-level functional, timing, and power issues during bring up.
Requirements
Master’s degree in Computer Science, Electrical Engineering, or equivalent.
Can work in a hybrid work environment.
8-15 years of experience in delivering complex, high performance high quality RTL designs.
Experience with Front End Chip integration and third-party IP integration.
Demonstrated experience in networking, high-performance computing, machine learning or related fields.
Proven track record of multiple silicon success.
Experience collaborating and managing external vendors.
Experience with designing/integrating high speed IO.
Networking stack experience including TCP/IP, RDMA and Ethernet.
Knowledge of PCIe, CPU interfaces and Serdes technology.
Working knowledge of scripting tools : Python, TCL.
Assets
Experience with FPGA development toolchain, including Place and Route, Floor planning and Timing Analysis is a plus.
The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a lead front-end design engineer, you will be a key part of the world-class team designing and developing the next generations of the Cerebras Wafer Scale Engine (WSE). \n\nThis role requires deep expertise in RTL design and integration, with a strong focus on delivering high-performance, power-efficient, and scalable solutions. The role also requires close collaboration and management of external ASIC vendor. You will collaborate closely with the design verification, physical design, software and system teams to bring innovative semiconductor architectures from concept to production, addressing the unique challenges of building WSE systems.\n\n \n\nResponsibilities\n\n - Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL development, Synthesis.\n\n - Managing external ASIC vendor through product development cycle.\n\n - Work closely with PD team members for design closure to meet PPA goals.\n\n - Work closely with Design verification and DFT teams for achieving the best functional and test coverage.\n\n - Work with software and system teams to understand opportunities to deliver optimal performance and feature set for the product.\n\n - Debug silicon-level functional, timing, and power issues during bring up.\n\nRequirements\n\n - Master’s degree in Computer Science, Electrical Engineering, or equivalent.\n\n - Can work in a hybrid work environment. \n\n - 8-15 years of experience in delivering complex, high performance high quality RTL designs.\n\n - Experience with Front End Chip integration and third-party IP integration.\n\n - Demonstrated experience in networking, high-performance computing, machine learning or related fields.\n\n - Proven track record of multiple silicon success.\n\n - Experience collaborating and managing external vendors.\n\n - Experience with designing/integrating high speed IO.\n\n - Networking stack experience including TCP/IP, RDMA and Ethernet.\n\n - Knowledge of PCIe, CPU interfaces and Serdes technology.\n\n - Working knowledge of scripting tools : Python, TCL.\n\nAssets\n\n - Experience with FPGA development toolchain, including Place and Route, Floor planning and Timing Analysis is a plus.\n\n The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"91fb96a9-1737-4d3d-ac73-ac2f6c40ec58","title":"Senior / Staff Technical Program Manager - Datacenter Capacity Delivery (E2E) ","department":"Hardware Departments","team":"Datacenters","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-06-03T04:40:21.041+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/91fb96a9-1737-4d3d-ac73-ac2f6c40ec58","applyUrl":"https://jobs.ashbyhq.com/cerebras/91fb96a9-1737-4d3d-ac73-ac2f6c40ec58/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
The DC Delivery E2E TPM is the single-threaded owner for delivering data center capacity from forecast → site strategy → design → construction → infrastructure readiness → go-live.
You will operate as the SSOT (Single Source of Truth) for delivery milestones, risks, and capacity outcomes while orchestrating cross-functional execution across internal teams and external partners. This is a frontier-scale role where ambiguity is high, timelines are compressed, and stakes are critical to company growth.
Responsibilities
End-to-End Capacity Delivery
Own delivery of AI-optimized data center capacity (colo, build-to-suit, retrofits, and owned facilities) from pre-contract planning through operational readiness.
Deliver MW-scale infrastructure aligned to aggressive GPU/AI system deployment targets.
Drive clarity from ambiguity—translate high-level demand signals into executable delivery programs.
Program Structuring & Execution
Decompose complex build programs into workstreams with clear owners, milestones, and deliverables.
Build integrated plans spanning real estate, power/energy, design, procurement, construction, and deployment.
Establish critical path visibility and aggressively manage schedule compression.
Cross-Functional Leadership
Orchestrate execution across:
Real estate & site selection
Power & energy strategy (utilities, PPAs, interconnects)
Data center design (MEP, liquid cooling, high-density racks)
Supply chain & long-lead equipment procurement
Construction & commissioning
Infrastructure deployment (rack/cluster install)
Networking & backbone connectivity
Security, compliance, and operations readiness
Act as the primary interface with colocation providers, EPCs, utilities, and key vendors.
Risk, Cost & Governance
Identify and drive resolution of critical risks, constraints, and blockers across power, equipment, permitting, and supply chain.
Own and maintain program budgets, CapEx forecasts, and capital allocation narratives.
Provide structured updates and escalation paths to executive leadership.
Demand & Capacity Planning Integration
Partner with capacity planning, AI infrastructure, and finance teams to translate model demand into site-level capacity strategies.
Align build plans with power availability, network topology, and hardware rollout schedules.
Continuously optimize for time-to-capacity and cost-per-MW / cost-per-GPU deployed.
Operational Excellence
Drive E2E improvements in delivery through:
Standardization of build and commissioning processes
Implementation of program tooling and dashboards
Post-mortems and lessons learned loops
Establish scalable mechanisms to support rapid global expansion.
Communication & Leadership
Serve as SSOT for program health, milestones, and risks.
Deliver concise, high-signal updates to senior executives.
Operate effectively across distributed teams with up to 50% travel.
Skills & Qualifications
12-15+ years in mission-critical facilities or data center operations
Experience managing multi-site, vendor-heavy environments
Strong expertise in electrical and mechanical systems
Proven track record in improving uptime and performance
Preferred Qualifications
Experience at hyperscalers (Google, Meta, Microsoft) or neo-cloud / AI infra companies (CoreWeave, Lambda, etc.).
Familiarity with high-density AI workloads (liquid cooling, >30kW racks, GPU clusters).
Experience with:
Utility engagement and power delivery constraints
Long-lead supply chain planning (transformers, switchgear, chillers)
Commissioning and data center handover processes
Ability to operate in high-growth, ambiguous environments with limited structure.
Strong executive presence and ability to influence without authority.
What sets you apart
Extreme ownership mindset — you treat capacity delivery as a personal SLA.
Ability to move fast without breaking systems, balancing urgency with rigor.
Comfort operating at the intersection of hardware, real estate, and software scaling demands.
Clear, structured communicator who can turn chaos into executable plans.
Bias for action with a track record of delivering results under pressure.
Location: US (preferred SF Bay Area / remote with travel)
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThe DC Delivery E2E TPM is the single-threaded owner for delivering data center capacity from forecast → site strategy → design → construction → infrastructure readiness → go-live.\n\nYou will operate as the SSOT (Single Source of Truth) for delivery milestones, risks, and capacity outcomes while orchestrating cross-functional execution across internal teams and external partners. This is a frontier-scale role where ambiguity is high, timelines are compressed, and stakes are critical to company growth.\n\nResponsibilities\n\nEnd-to-End Capacity Delivery\n\n - Own delivery of AI-optimized data center capacity (colo, build-to-suit, retrofits, and owned facilities) from pre-contract planning through operational readiness.\n\n - Deliver MW-scale infrastructure aligned to aggressive GPU/AI system deployment targets.\n\n - Drive clarity from ambiguity—translate high-level demand signals into executable delivery programs.\n\nProgram Structuring & Execution\n\n - Decompose complex build programs into workstreams with clear owners, milestones, and deliverables.\n\n - Build integrated plans spanning real estate, power/energy, design, procurement, construction, and deployment.\n\n - Establish critical path visibility and aggressively manage schedule compression.\n\nCross-Functional Leadership\n\n - Orchestrate execution across:\n \n - Real estate & site selection\n \n - Power & energy strategy (utilities, PPAs, interconnects)\n \n - Data center design (MEP, liquid cooling, high-density racks)\n \n - Supply chain & long-lead equipment procurement\n \n - Construction & commissioning\n \n - Infrastructure deployment (rack/cluster install)\n \n - Networking & backbone connectivity\n \n - Security, compliance, and operations readiness\n\n - Act as the primary interface with colocation providers, EPCs, utilities, and key vendors.\n\nRisk, Cost & Governance\n\n - Identify and drive resolution of critical risks, constraints, and blockers across power, equipment, permitting, and supply chain.\n\n - Own and maintain program budgets, CapEx forecasts, and capital allocation narratives.\n\n - Provide structured updates and escalation paths to executive leadership.\n\nDemand & Capacity Planning Integration\n\n - Partner with capacity planning, AI infrastructure, and finance teams to translate model demand into site-level capacity strategies.\n\n - Align build plans with power availability, network topology, and hardware rollout schedules.\n\n - Continuously optimize for time-to-capacity and cost-per-MW / cost-per-GPU deployed.\n\nOperational Excellence\n\n - Drive E2E improvements in delivery through:\n \n - Standardization of build and commissioning processes\n \n - Implementation of program tooling and dashboards\n \n - Post-mortems and lessons learned loops\n\n - Establish scalable mechanisms to support rapid global expansion.\n\nCommunication & Leadership\n\n - Serve as SSOT for program health, milestones, and risks.\n\n - Deliver concise, high-signal updates to senior executives.\n\n - Operate effectively across distributed teams with up to 50% travel.\n\nSkills & Qualifications\n\n - 12-15+ years in mission-critical facilities or data center operations\n\n - Experience managing multi-site, vendor-heavy environments\n\n - Strong expertise in electrical and mechanical systems\n\n - Proven track record in improving uptime and performance\n\nPreferred Qualifications \n\n - Experience at hyperscalers (Google, Meta, Microsoft) or neo-cloud / AI infra companies (CoreWeave, Lambda, etc.).\n\n - Familiarity with high-density AI workloads (liquid cooling, >30kW racks, GPU clusters).\n\n - Experience with:\n \n - Utility engagement and power delivery constraints\n \n - Long-lead supply chain planning (transformers, switchgear, chillers)\n \n - Commissioning and data center handover processes\n\n - Ability to operate in high-growth, ambiguous environments with limited structure.\n\n - Strong executive presence and ability to influence without authority.\n\nWhat sets you apart \n\n - Extreme ownership mindset — you treat capacity delivery as a personal SLA.\n\n - Ability to move fast without breaking systems, balancing urgency with rigor.\n\n - Comfort operating at the intersection of hardware, real estate, and software scaling demands.\n\n - Clear, structured communicator who can turn chaos into executable plans.\n\n - Bias for action with a track record of delivering results under pressure.\n\nLocation: US (preferred SF Bay Area / remote with travel)\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"92939082-317e-41ac-aa98-29dcf9eb5422","title":"Manufacturing Bring-up Engineer L2 ","department":"Manufacturing Departments","team":"Manufacturing","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-03-02T22:13:28.678+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/92939082-317e-41ac-aa98-29dcf9eb5422","applyUrl":"https://jobs.ashbyhq.com/cerebras/92939082-317e-41ac-aa98-29dcf9eb5422/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are seeking a highly skilled and motivated Manufacturing Bring-up Engineer to join our team. As the Manufacturing Bring-up Engineer you will support our system level bring-up process execution, implementation, and evolution in the manufacturing pipeline. This is a high visibility role that requires strong technical expertise, coordination, and collaboration to deliver our product from manufacturing to the customer.
Responsibilities
Support the Cerebras manufacturing bring-up process execution to configure, test, and validate system performance prior to customer shipment
Collaborate cross-functionally with Asic, SW, Diagnostics, and QA teams to further automate and streamline the workflow for optimal manufacturing efficiency
Troubleshoot and resolve technical issues during system bring-up across Asic, SW, and QA domains
Design and implement efficient processes to manage and track system bring-up status and progress
Track and report on critical bring-up metrics to drive continuous improvement
Implement further SW automation and efficiencies to effectively scale the manufacturing bring-up process in support of the manufacturing roadmap
Skills & Qualifications
BS or MS in EE, ECE, CS or equivalent work experience
3+ years of industry experience in an operations environment
Experience in hardware bring-up and the debug of complex systems
Working knowledge and experience in Asic bringup and test processes
Working knowledge of scripting in languages such as Python and/or Perl
Proven experience in system bring-up and validation of complex computer systems or equivalent technologies
Understanding of computer system architecture and hardware components
Proficiency in scripting and automation tools for system bringup
Excellent problem-solving and communication skills with the ability to work collaboratively in a fast-paced environment
Very strong coordination and collaboration skills to manage a business-critical workflow directly in support of customer demand
Preferred:
Familiarity in creating test and s/w infrastructure at large scale
Working across global time zones
Location
Bangalore, India/Toronto, Canada/ Sunnyvale, California.
The base salary range for this position is $170,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role \n\nWe are seeking a highly skilled and motivated Manufacturing Bring-up Engineer to join our team. As the Manufacturing Bring-up Engineer you will support our system level bring-up process execution, implementation, and evolution in the manufacturing pipeline. This is a high visibility role that requires strong technical expertise, coordination, and collaboration to deliver our product from manufacturing to the customer. \n\nResponsibilities \n\n - Support the Cerebras manufacturing bring-up process execution to configure, test, and validate system performance prior to customer shipment \n\n - Collaborate cross-functionally with Asic, SW, Diagnostics, and QA teams to further automate and streamline the workflow for optimal manufacturing efficiency \n\n - Troubleshoot and resolve technical issues during system bring-up across Asic, SW, and QA domains \n\n - Design and implement efficient processes to manage and track system bring-up status and progress \n\n - Track and report on critical bring-up metrics to drive continuous improvement \n\n - Implement further SW automation and efficiencies to effectively scale the manufacturing bring-up process in support of the manufacturing roadmap \n\n \n\nSkills & Qualifications \n\n - BS or MS in EE, ECE, CS or equivalent work experience \n\n - 3+ years of industry experience in an operations environment \n\n - Experience in hardware bring-up and the debug of complex systems \n\n - Working knowledge and experience in Asic bringup and test processes \n\n - Working knowledge of scripting in languages such as Python and/or Perl \n\n - Proven experience in system bring-up and validation of complex computer systems or equivalent technologies \n\n - Understanding of computer system architecture and hardware components \n\n - Proficiency in scripting and automation tools for system bringup \n\n - Excellent problem-solving and communication skills with the ability to work collaboratively in a fast-paced environment \n\n - Very strong coordination and collaboration skills to manage a business-critical workflow directly in support of customer demand \n\nPreferred: \n\n - Familiarity in creating test and s/w infrastructure at large scale \n\n - Working across global time zones \n\nLocation \n\nBangalore, India/Toronto, Canada/ Sunnyvale, California.\n\nThe base salary range for this position is $170,000 to $230,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"987d7f64-c957-4c8f-b89d-2f9d64738507","title":"CoDesign & NextGen - New College Grad ","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-01-07T04:02:02.311+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/987d7f64-c957-4c8f-b89d-2f9d64738507","applyUrl":"https://jobs.ashbyhq.com/cerebras/987d7f64-c957-4c8f-b89d-2f9d64738507/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
Engineers in the CoDesign and NextGen organization work at the interface of software and hardware helping everything from high performance kernel design, next generation ASIC performance modeling and tuning, new system bringup and software tuning, system robustness and simulations.
As an new engineer you'll be expected to learn the Cerebras products and platforms end to end starting at the base layer of programming the Wafer Scale Engine through kernel development, modeling performance for our software products and validating the work through exercising it on both actual hardware and simulations.
Skills & Qualifications
MS/BS in Computer Engineer, Electrical Engineering or Computer Science
Strong background in computer architecture
Strong analytical and problem solving mindset
Exposure to CPU/GPU Architecture and programming models
Experience working on CPU/GPU simulators
Exposure to performance profiling and debug on any system pipeline
Experience with C++ and Python
Exposure to and basic understanding of machine learning is desired
Location
This is a full-time, in-office position based in Sunnyvale, CA. We offer relocation support for candidates relocating to the Bay Area.
Base salary range: $145,000-$155,000 annually, depending on experience, skills, and qualifications, plus equity.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nEngineers in the CoDesign and NextGen organization work at the interface of software and hardware helping everything from high performance kernel design, next generation ASIC performance modeling and tuning, new system bringup and software tuning, system robustness and simulations.\n\n \n\nAs an new engineer you'll be expected to learn the Cerebras products and platforms end to end starting at the base layer of programming the Wafer Scale Engine through kernel development, modeling performance for our software products and validating the work through exercising it on both actual hardware and simulations.\n\nSkills & Qualifications\n\n - MS/BS in Computer Engineer, Electrical Engineering or Computer Science\n\n - Strong background in computer architecture\n\n - Strong analytical and problem solving mindset\n\n - Exposure to CPU/GPU Architecture and programming models\n\n - Experience working on CPU/GPU simulators\n\n - Exposure to performance profiling and debug on any system pipeline\n\n - Experience with C++ and Python\n\n - Exposure to and basic understanding of machine learning is desired\n\nLocation\n\nThis is a full-time, in-office position based in Sunnyvale, CA. We offer relocation support for candidates relocating to the Bay Area.\n\nBase salary range: $145,000-$155,000 annually, depending on experience, skills, and qualifications, plus equity. \n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"98ccea5d-d67a-4b58-a44a-168eb5012fe6","title":"AI Infrastructure Operations Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-02-09T21:36:36.241+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/98ccea5d-d67a-4b58-a44a-168eb5012fe6","applyUrl":"https://jobs.ashbyhq.com/cerebras/98ccea5d-d67a-4b58-a44a-168eb5012fe6/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
The AI Infrastructure Operations Engineer (SiteOps) is an entry-level individual contributor role focused on the deployment, bring-up, monitoring, and first-line troubleshooting of Cerebras AI infrastructure in data center environments. The role supports CS systems, cluster server hardware, cluster networking hardware, and hardware telemetry and monitoring tools.
Support reliable operation and scale-out of Cerebras AI clusters by executing defined hardware bring-up and validation procedures, monitoring telemetry, performing first-line troubleshooting, and escalating issues using established workflows.
Responsibilities
Assist with deployment and bring-up of CS-X systems, cluster servers, and networking hardware;
• Execute power-on sequencing, readiness checks, and validation tests.
• Monitor hardware telemetry, alerts, and dashboards.
• Perform first-line troubleshooting and structured escalation.
• Collect logs, telemetry, and observations during incidents.
Incident Support & Tooling
Participate in incident response under senior engineer guidance;
• Use existing monitoring, telemetry, and incident tracking tools.
• Provide feedback on tooling and process gaps.
Learning & Development
Build working knowledge of Cerebras system architecture;
• Learn cluster hardware and networking fundamentals.
• Shadow senior engineers during complex debugging.
• Progress toward independent ownership of defined workflows.
Explicit Non-Responsibilities
No people management;
• No final escalation authority.
• No ownership of cluster architecture, hardware design, or tooling architecture.
Required Qualifications
Bachelor’s degree in a relevant engineering field or equivalent experience; 0–3 years experience in hardware operations, systems engineering, or datacenter environments; basic familiarity with server hardware, networking fundamentals, and Linux systems.
Preferred Qualifications
Internship or early-career experience in datacenter or hardware lab environments; exposure to monitoring or telemetry systems; comfort working in data centers.
What Success Looks Like
Consistent and correct execution of hardware bring-up procedures, early identification and escalation of issues, improving documentation quality, and clear progression toward more independent operational responsibility.
Career Path
This role progresses naturally toward Senior and Principal IC roles within AI Infrastructure Operations (SiteOps), with an optional management track.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThe AI Infrastructure Operations Engineer (SiteOps) is an entry-level individual contributor role focused on the deployment, bring-up, monitoring, and first-line troubleshooting of Cerebras AI infrastructure in data center environments. The role supports CS systems, cluster server hardware, cluster networking hardware, and hardware telemetry and monitoring tools.\n\nSupport reliable operation and scale-out of Cerebras AI clusters by executing defined hardware bring-up and validation procedures, monitoring telemetry, performing first-line troubleshooting, and escalating issues using established workflows.\n\nResponsibilities\n\n - Assist with deployment and bring-up of CS-X systems, cluster servers, and networking hardware;\n • Execute power-on sequencing, readiness checks, and validation tests.\n • Monitor hardware telemetry, alerts, and dashboards.\n • Perform first-line troubleshooting and structured escalation.\n • Collect logs, telemetry, and observations during incidents.\n\nIncident Support & Tooling\n\n - Participate in incident response under senior engineer guidance;\n • Use existing monitoring, telemetry, and incident tracking tools.\n • Provide feedback on tooling and process gaps.\n\nLearning & Development\n\n - Build working knowledge of Cerebras system architecture;\n • Learn cluster hardware and networking fundamentals.\n • Shadow senior engineers during complex debugging.\n • Progress toward independent ownership of defined workflows.\n\nExplicit Non-Responsibilities\n\n - No people management;\n • No final escalation authority.\n • No ownership of cluster architecture, hardware design, or tooling architecture.\n\nRequired Qualifications\n\nBachelor’s degree in a relevant engineering field or equivalent experience; 0–3 years experience in hardware operations, systems engineering, or datacenter environments; basic familiarity with server hardware, networking fundamentals, and Linux systems.\n\nPreferred Qualifications\n\nInternship or early-career experience in datacenter or hardware lab environments; exposure to monitoring or telemetry systems; comfort working in data centers.\n\nWhat Success Looks Like\n\nConsistent and correct execution of hardware bring-up procedures, early identification and escalation of issues, improving documentation quality, and clear progression toward more independent operational responsibility.\n\nCareer Path\n\nThis role progresses naturally toward Senior and Principal IC roles within AI Infrastructure Operations (SiteOps), with an optional management track.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"99c289fa-8fc6-49f7-b7e8-78ac4e9d99ac","title":"Software Engineer - New Grad 2026","department":"Software","team":"Software","employmentType":"FullTime","location":"Toronto Office","secondaryLocations":[],"publishedAt":"2026-05-11T19:38:35.637+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/99c289fa-8fc6-49f7-b7e8-78ac4e9d99ac","applyUrl":"https://jobs.ashbyhq.com/cerebras/99c289fa-8fc6-49f7-b7e8-78ac4e9d99ac/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As a New Graduate Software Engineer, you will collaborate with world-class engineers to solve real-world challenges across the software stack. You will contribute to software systems that directly impact performance, scalability, reliability, and usability of next-generation AI infrastructure.
This role is ideal for candidates with a strong interest in systems programming, networking, embedded systems, distributed infrastructure, or performance-oriented software engineering. Our teams work very closely with hardware, so candidates with experience primarily focused on higher-level application development or AI applications may be less aligned with the nature of this work.
You will gain hands-on experience working across multiple layers of a fully integrated AI-accelerated system, including advanced hardware interfaces, low-level infrastructure, distributed systems, compilers, and ML frameworks.
Collaborate with experienced engineers on real-world systems and infrastructure challenges.
Design, implement, test, and debug software solutions that directly impact system performance and reliability.
Contribute to low-level software components interacting closely with hardware and networking infrastructure.
Learn and contribute across multiple layers of a fully integrated AI-accelerated platform.
Participate in debugging, performance optimization, and system bring-up activities.
Develop tools and infrastructure to improve observability, reliability, and scalability.
Work cross-functionally with hardware, firmware, compiler, and infrastructure teams.
Recently graduated or currently enrolled in a university program in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline (graduating in 2026).
Proficiency in C/C++ programming languages
Interest or exposure to systems/socket programming, networking, embedded systems, operating systems, device drivers, distributed systems, or network performance.
Desire to work close to hardware/network and learn low-level engineering concepts.
Detail-oriented but keen to learn the bigger picture and step out of comfort zone.
Excellent communication and collaboration skills.
Hybrid role based in Toronto, ON, or Sunnyvale CA
Experience with Linux systems programming or debugging tools.
Familiarity with TCP/RDMA protocols, RPCs, and packet trace tools such as Wireshark
Exposure to networking concepts, device drivers, embedded systems, or distributed infrastructure.
Familiarity with performance optimization or concurrent programming concepts.
Interest in large-scale AI infrastructure and accelerated computing systems.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nAs a New Graduate Software Engineer, you will collaborate with world-class engineers to solve real-world challenges across the software stack. You will contribute to software systems that directly impact performance, scalability, reliability, and usability of next-generation AI infrastructure.\n\nThis role is ideal for candidates with a strong interest in systems programming, networking, embedded systems, distributed infrastructure, or performance-oriented software engineering. Our teams work very closely with hardware, so candidates with experience primarily focused on higher-level application development or AI applications may be less aligned with the nature of this work.\n\nYou will gain hands-on experience working across multiple layers of a fully integrated AI-accelerated system, including advanced hardware interfaces, low-level infrastructure, distributed systems, compilers, and ML frameworks.\n\n\nRESPONSIBILITIES\n\n - Collaborate with experienced engineers on real-world systems and infrastructure challenges.\n\n - Design, implement, test, and debug software solutions that directly impact system performance and reliability.\n\n - Contribute to low-level software components interacting closely with hardware and networking infrastructure.\n\n - Learn and contribute across multiple layers of a fully integrated AI-accelerated platform.\n\n - Participate in debugging, performance optimization, and system bring-up activities.\n\n - Develop tools and infrastructure to improve observability, reliability, and scalability.\n\n - Work cross-functionally with hardware, firmware, compiler, and infrastructure teams.\n\n\nREQUIRED QUALIFICATIONS\n\n - Recently graduated or currently enrolled in a university program in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline (graduating in 2026).\n\n - Proficiency in C/C++ programming languages\n\n - Interest or exposure to systems/socket programming, networking, embedded systems, operating systems, device drivers, distributed systems, or network performance.\n\n - Desire to work close to hardware/network and learn low-level engineering concepts.\n\n - Detail-oriented but keen to learn the bigger picture and step out of comfort zone.\n\n - Excellent communication and collaboration skills.\n\n - Hybrid role based in Toronto, ON, or Sunnyvale CA\n\n\nASSETS\n\n - Experience with Linux systems programming or debugging tools.\n\n - Familiarity with TCP/RDMA protocols, RPCs, and packet trace tools such as Wireshark\n\n - Exposure to networking concepts, device drivers, embedded systems, or distributed infrastructure.\n\n - Familiarity with performance optimization or concurrent programming concepts.\n\n - Interest in large-scale AI infrastructure and accelerated computing systems.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"9f6c08a7-66c5-4b54-9951-07b2d33b3beb","title":"Compute Server Platform Architect","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-02-18T16:45:40.943+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/9f6c08a7-66c5-4b54-9951-07b2d33b3beb","applyUrl":"https://jobs.ashbyhq.com/cerebras/9f6c08a7-66c5-4b54-9951-07b2d33b3beb/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Compute / Server Platform Architect on the Cluster Architecture Team, you will own the server-side platform architecture that enables Cerebras CS3-based AI clusters (training and inference) to deliver predictable performance, scalability, and reliability. Our accelerators are network-attached, so the x86 server fleet is a first-class part of the end-to-end system: it runs critical-path runtime functions (for example orchestration, prompt caching, and IO/control services) and must be co-designed with software for token-level latency, throughput, and cost efficiency. You will translate workload behavior into CPU, memory, IO, PCIe, and host-networking requirements, drive platform evaluations with vendors, and provide technical leadership through qualification and production adoption in close partnership with other function leaders and TPMs.
Responsibilities
Own the architecture for all server roles in Cerebras clusters, including definitions of server types, configurations, and lifecycle strategy.
Define and maintain server formulas (counts and ratios per CS-3 count, cluster size, and workload type) including capacity planning and headroom policy.
Specify platform configurations: CPU SKU and core strategy, our vendor roadmap (e.g., AMD, Intel, ARM), memory topology (channels, DIMM type, capacity), PCIe topology and lane budgeting, NIC selection/placement, and local NVMe policy where applicable.
Translate software and runtime flows into measurable hardware requirements (CPU utilization, memory bandwidth/latency, bursty IO patterns, queueing and concurrency limits) and communicate clear guardrails back to software teams.
Develop performance and scaling models; validate with microbenchmarks and workload-level experiments; identify bottlenecks and drive cross-stack fixes.
Define the OS, BIOS, firmware, and driver baseline for each server type; there are other teams that follow these recommendations and apply them on our fleet.
Stay current on emerging server technologies (CPU generations, new memory technologies, CXL, NVMe evolutions, SmartNIC/DPU capabilities where relevant) and run proof-of-concept evaluations to determine when to adopt.
Lead technical vendor engagements (OEM/ODM and component vendors): influence roadmap, request platform knobs, and drive joint debugging on performance or reliability issues.
Define qualification and acceptance criteria (performance, stability, operability) and partner with the Infrastructure Hardware TPM to execute qualification plans and land changes cleanly into production.
Support bring-up and rare deployment debugging in lab and staging environments; drive root-cause analysis for regressions spanning firmware, drivers, OS, and runtime behavior.
Skills and Qualifications
PhD. in Computer Science or Electrical/Computer Engineering and + 8 years industry experience, or Master’s/Bachelor’s in CS or EE + 10 years industry experience.
5+ years of experience in server platform architecture, systems performance engineering, or large-scale infrastructure design for AI/ML, HPC, or performance-sensitive distributed systems.
Deep understanding of x86 server architecture: CPU microarchitecture basics, cache hierarchies, NUMA, memory controllers/channels, and memory bandwidth vs latency tradeoffs.
Strong Linux systems knowledge: profiling and performance analysis, scheduling and syscall overheads, memory management behavior, and practical tuning methodology.
Experience reasoning about high-performance IO paths, including NIC behavior at a systems level, RDMA/RoCE concepts, and NVMe performance characteristics.
Proven ability to create capacity and performance models and validate them empirically with a rigorous benchmarking plan.
Experience working directly with vendors/partners to evaluate platforms, drive issue resolution, and influence roadmaps.
Strong cross-functional communication skills and ability to drive technical decisions through clear tradeoff documents and reviews.
Familiarity with application and system software (C, C++, Python).
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Compute / Server Platform Architect on the Cluster Architecture Team, you will own the server-side platform architecture that enables Cerebras CS3-based AI clusters (training and inference) to deliver predictable performance, scalability, and reliability. Our accelerators are network-attached, so the x86 server fleet is a first-class part of the end-to-end system: it runs critical-path runtime functions (for example orchestration, prompt caching, and IO/control services) and must be co-designed with software for token-level latency, throughput, and cost efficiency. You will translate workload behavior into CPU, memory, IO, PCIe, and host-networking requirements, drive platform evaluations with vendors, and provide technical leadership through qualification and production adoption in close partnership with other function leaders and TPMs.\n\n \n\nResponsibilities\n\n - Own the architecture for all server roles in Cerebras clusters, including definitions of server types, configurations, and lifecycle strategy.\n\n - Define and maintain server formulas (counts and ratios per CS-3 count, cluster size, and workload type) including capacity planning and headroom policy.\n\n - Specify platform configurations: CPU SKU and core strategy, our vendor roadmap (e.g., AMD, Intel, ARM), memory topology (channels, DIMM type, capacity), PCIe topology and lane budgeting, NIC selection/placement, and local NVMe policy where applicable.\n\n - Translate software and runtime flows into measurable hardware requirements (CPU utilization, memory bandwidth/latency, bursty IO patterns, queueing and concurrency limits) and communicate clear guardrails back to software teams.\n\n - Develop performance and scaling models; validate with microbenchmarks and workload-level experiments; identify bottlenecks and drive cross-stack fixes.\n\n - Define the OS, BIOS, firmware, and driver baseline for each server type; there are other teams that follow these recommendations and apply them on our fleet.\n\n - Stay current on emerging server technologies (CPU generations, new memory technologies, CXL, NVMe evolutions, SmartNIC/DPU capabilities where relevant) and run proof-of-concept evaluations to determine when to adopt.\n\n - Lead technical vendor engagements (OEM/ODM and component vendors): influence roadmap, request platform knobs, and drive joint debugging on performance or reliability issues.\n\n - Define qualification and acceptance criteria (performance, stability, operability) and partner with the Infrastructure Hardware TPM to execute qualification plans and land changes cleanly into production.\n\n - Support bring-up and rare deployment debugging in lab and staging environments; drive root-cause analysis for regressions spanning firmware, drivers, OS, and runtime behavior.\n\nSkills and Qualifications\n\n - PhD. in Computer Science or Electrical/Computer Engineering and + 8 years industry experience, or Master’s/Bachelor’s in CS or EE + 10 years industry experience.\n\n - 5+ years of experience in server platform architecture, systems performance engineering, or large-scale infrastructure design for AI/ML, HPC, or performance-sensitive distributed systems.\n\n - Deep understanding of x86 server architecture: CPU microarchitecture basics, cache hierarchies, NUMA, memory controllers/channels, and memory bandwidth vs latency tradeoffs.\n\n - Strong Linux systems knowledge: profiling and performance analysis, scheduling and syscall overheads, memory management behavior, and practical tuning methodology.\n\n - Experience reasoning about high-performance IO paths, including NIC behavior at a systems level, RDMA/RoCE concepts, and NVMe performance characteristics.\n\n - Proven ability to create capacity and performance models and validate them empirically with a rigorous benchmarking plan.\n\n - Experience working directly with vendors/partners to evaluate platforms, drive issue resolution, and influence roadmaps.\n\n - Strong cross-functional communication skills and ability to drive technical decisions through clear tradeoff documents and reviews.\n\n - Familiarity with application and system software (C, C++, Python).\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"a939e310-95ef-48b0-963c-b55dd8376d9b","title":"Senior Technical Program Manager – AI Infrastructure, Site Operations","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2025-12-16T19:07:36.487+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/a939e310-95ef-48b0-963c-b55dd8376d9b","applyUrl":"https://jobs.ashbyhq.com/cerebras/a939e310-95ef-48b0-963c-b55dd8376d9b/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
This Sr. TPM role owns site and data center operations programs supporting Cerebras’ AI Cloud and customer deployments. The position sits at Sunnyvale HQ and works closely with Hardware Engineering, Inference Engineering, and Operations leadership to ensure Cerebras systems are reliably deployed, operated, and scaled.
This is a highly technical, execution-focused TPM role with strong emphasis on operational readiness, cross-functional coordination, and metrics/KPIs.
Responsibilities
Own end-to-end technical programs for data center and site operations
Act as single-threaded owner across:
Hardware & Systems Engineering
AI Cloud Infrastructure & Operations
Network & Storage Engineering
Facilities, power, cooling, and colo partners
Drive site readiness for Cerebras Wafer-Scale Engine systems
Partner on installation, commissioning, change management, and break/fix workflows
Lead incident reviews and postmortems; ensure corrective actions are closed
Define and own operational metrics and KPIs, including:
Availability and reliability
Incident rate, severity, MTTR / MTTD
Deployment readiness and time-to-service
Capacity and operational risk
Build executive-level dashboards and reporting
Establish program governance, risk tracking, and RACI clarity
Present program status, metrics, and operational risks to senior leadership
Required Background
8+ years in Technical Program Management, Infrastructure Ops, or Data Center Ops
Experience leading large, cross-functional infrastructure programs
Strong understanding of:
Data center power and cooling fundamentals
Network and storage basics
Hardware-centric platforms
Proven ability to define and operationalize metrics
Strong written and executive-level communication skills
Preferred Experience
AI/ML, HPC, or accelerator-based infrastructure
High-density and/or liquid-cooled data centers
Working with colocation providers and facilities teams
Incident management, reliability, or service operations background
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThis Sr. TPM role owns site and data center operations programs supporting Cerebras’ AI Cloud and customer deployments. The position sits at Sunnyvale HQ and works closely with Hardware Engineering, Inference Engineering, and Operations leadership to ensure Cerebras systems are reliably deployed, operated, and scaled.\n\nThis is a highly technical, execution-focused TPM role with strong emphasis on operational readiness, cross-functional coordination, and metrics/KPIs.\n\nResponsibilities \n\n - Own end-to-end technical programs for data center and site operations\n\n - Act as single-threaded owner across:\n \n - Hardware & Systems Engineering\n \n - AI Cloud Infrastructure & Operations\n \n - Network & Storage Engineering\n \n - Facilities, power, cooling, and colo partners\n\n - Drive site readiness for Cerebras Wafer-Scale Engine systems\n\n - Partner on installation, commissioning, change management, and break/fix workflows\n\n - Lead incident reviews and postmortems; ensure corrective actions are closed\n\n - Define and own operational metrics and KPIs, including:\n \n - Availability and reliability\n \n - Incident rate, severity, MTTR / MTTD\n \n - Deployment readiness and time-to-service\n \n - Capacity and operational risk\n\n - Build executive-level dashboards and reporting\n\n - Establish program governance, risk tracking, and RACI clarity\n\n - Present program status, metrics, and operational risks to senior leadership\n\nRequired Background \n\n - 8+ years in Technical Program Management, Infrastructure Ops, or Data Center Ops\n\n - Experience leading large, cross-functional infrastructure programs\n\n - Strong understanding of:\n \n - Data center power and cooling fundamentals\n \n - Network and storage basics\n \n - Hardware-centric platforms\n\n - Proven ability to define and operationalize metrics\n\n - Strong written and executive-level communication skills\n\nPreferred Experience \n\n - AI/ML, HPC, or accelerator-based infrastructure\n\n - High-density and/or liquid-cooled data centers\n\n - Working with colocation providers and facilities teams\n\n - Incident management, reliability, or service operations background\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"a98bb5ba-31af-4c12-a38b-719ce95a6f33","title":"Senior WAN Network Engineer ","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-03-30T20:27:20.819+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/a98bb5ba-31af-4c12-a38b-719ce95a6f33","applyUrl":"https://jobs.ashbyhq.com/cerebras/a98bb5ba-31af-4c12-a38b-719ce95a6f33/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are seeking a highly skilled WAN Network Engineer to design, implement, manage, and optimize global connectivity. The ideal candidate will have strong experience with carrier networks, routing protocols, and network security, and will play a critical role in ensuring high availability, performance, and reliability of global network services.
Responsibilities
Design, deploy, and maintain WAN network across leased lines and dark fiber for low latency and 99.999% availability.
Collaborate with telecom providers and ISPs for circuit provisioning, upgrades, and issue resolution.
Configure, troubleshoot, and optimize security and routing protocols (IPSec Tunnels, MACsec, BGP, VXLAN, EVPN).
Monitor WAN performance, latency, packet loss, capacity utilization. Analyze traffic patterns to predict growth and trigger circuit upgrades or hardware refreshes before bottlenecks occur.
Implement redundancy, failover, QoS, and traffic engineering to ensure business continuity.
Participate in network modernization and cloud connectivity projects (AWS, Azure, GCP).
Provide Tier 3 support for WAN-related incidents and root cause analysis.
Develop and maintain network documentation, diagrams, and standard operating procedures.
Use Python, Ansible, or Terraform to deploy configurations and manage network state at scale.
Support network security initiatives including site-to-site VPNs and perimeter connectivity. Ensure compliance with security, governance, and operational best practices.
Requirements
Bachelor’s degree in Computer Science, Electrical Engineering, or Computer Engineering. Master’s degree is preferred.
6+ years of experience in WAN network engineering, or Service Provider network, or Hyper-scale Data Center environment.
Industry certifications such as, CCIE or JNCIE. Strong knowledge of BGP routing protocols and WAN technologies.
Experience with major network vendors such as Arista, Cisco, Juniper, or Palo Alto.
Strong troubleshooting and analytical skills, and excellent communication and documentation skills.
Experience with cloud networking and hybrid network architectures.
Expertise with network automation tools (Python, Ansible, Terraform).
Knowledge of network monitoring tools (SolarWinds, Kentik, ThousandEyes, or similar).
Ability to participate in on-call rotation and after-hours maintenance.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nWe are seeking a highly skilled WAN Network Engineer to design, implement, manage, and optimize global connectivity. The ideal candidate will have strong experience with carrier networks, routing protocols, and network security, and will play a critical role in ensuring high availability, performance, and reliability of global network services.\n\nResponsibilities\n\n - Design, deploy, and maintain WAN network across leased lines and dark fiber for low latency and 99.999% availability. \n\n - Collaborate with telecom providers and ISPs for circuit provisioning, upgrades, and issue resolution.\n\n - Configure, troubleshoot, and optimize security and routing protocols (IPSec Tunnels, MACsec, BGP, VXLAN, EVPN). \n\n - Monitor WAN performance, latency, packet loss, capacity utilization. Analyze traffic patterns to predict growth and trigger circuit upgrades or hardware refreshes before bottlenecks occur.\n\n - Implement redundancy, failover, QoS, and traffic engineering to ensure business continuity.\n\n - Participate in network modernization and cloud connectivity projects (AWS, Azure, GCP).\n\n - Provide Tier 3 support for WAN-related incidents and root cause analysis.\n\n - Develop and maintain network documentation, diagrams, and standard operating procedures.\n\n - Use Python, Ansible, or Terraform to deploy configurations and manage network state at scale.\n\n - Support network security initiatives including site-to-site VPNs and perimeter connectivity. Ensure compliance with security, governance, and operational best practices.\n\nRequirements\n\n - Bachelor’s degree in Computer Science, Electrical Engineering, or Computer Engineering. Master’s degree is preferred. \n\n - 6+ years of experience in WAN network engineering, or Service Provider network, or Hyper-scale Data Center environment.\n\n - Industry certifications such as, CCIE or JNCIE. Strong knowledge of BGP routing protocols and WAN technologies.\n\n - Experience with major network vendors such as Arista, Cisco, Juniper, or Palo Alto.\n\n - Strong troubleshooting and analytical skills, and excellent communication and documentation skills.\n\n - Experience with cloud networking and hybrid network architectures.\n\n - Expertise with network automation tools (Python, Ansible, Terraform).\n\n - Knowledge of network monitoring tools (SolarWinds, Kentik, ThousandEyes, or similar).\n\n - Ability to participate in on-call rotation and after-hours maintenance.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ae5daf29-d7d0-440e-b41f-c6f0a67489f3","title":"Site Reliability Engineer - Ops & Automation","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2025-10-14T20:24:04.050+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/ae5daf29-d7d0-440e-b41f-c6f0a67489f3","applyUrl":"https://jobs.ashbyhq.com/cerebras/ae5daf29-d7d0-440e-b41f-c6f0a67489f3/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role:
We are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE), helping deliver infrastructure for frontier-class models from leading model builders such as OpenAI.
This role offers immediate ownership of real production systems at a growing scale, direct mentorship from seasoned engineers, and close collaboration with incoming Staff SREs who will focus on long-term automation. After ~1 month of shared hands-on operations with the Staff engineers, you’ll primarily operate the current setup, bring up new capacity in high-stakes environments and help bring new continuous delivery pipelines into production use.
If you thrive in high-ownership SRE roles at scale and want to help shape a team from the ground up in cutting-edge AI Inference infrastructure, this is your chance.
This role does not require 24/7 on-call rotations.
Key Responsibilities
Remain hands-on with operational execution (releases, capacity changes, cluster upgrades) over the next year as we build robust continuous delivery pipelines and self-service capabilities
Contribute to the development of self-service CD pipelines for key workflows using our stack: Kubernetes, Bazel, Prometheus/Grafana/InfluxDB, Python, and Go.
Build reusable automation and internal developer tools that minimize operational toil and cross-team friction
Develop and extend telemetry, observability and alerting solutions to ensure operational reliability at scale
Collaborate with Cluster Ops and development teams to identify high-impact automation opportunities and iterate quickly
Contribute to reliability practices (SLOs, post-mortems, capacity planning)
Required Experience & Skills
2-4+ years in SRE with a strong operations or automation focus
Production Kubernetes experience
Solid Python or Go for building tools and automation
Proficiency with Prometheus, Grafana, and observability-driven workflows
Ability to measure and communicate impact – reliability metrics, operational toil, velocity gains
Nice-to-Have
Hands-on GitOps expertise, Argo CD / Flux or equivalent, is a plus
Experience with building continuous delivery pipelines is a strong plus
Experience with Bazel or similar build systems is a strong plus.
Familiarity with capacity planning, on-prem or multi-datacenter environments
Location
SF Bay Area
Toronto
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role:\n\nWe are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE), helping deliver infrastructure for frontier-class models from leading model builders such as OpenAI.\n\nThis role offers immediate ownership of real production systems at a growing scale, direct mentorship from seasoned engineers, and close collaboration with incoming Staff SREs who will focus on long-term automation. After ~1 month of shared hands-on operations with the Staff engineers, you’ll primarily operate the current setup, bring up new capacity in high-stakes environments and help bring new continuous delivery pipelines into production use.\n\nIf you thrive in high-ownership SRE roles at scale and want to help shape a team from the ground up in cutting-edge AI Inference infrastructure, this is your chance.\n\nThis role does not require 24/7 on-call rotations.\n\nKey Responsibilities\n\n - Remain hands-on with operational execution (releases, capacity changes, cluster upgrades) over the next year as we build robust continuous delivery pipelines and self-service capabilities\n\n - Contribute to the development of self-service CD pipelines for key workflows using our stack: Kubernetes, Bazel, Prometheus/Grafana/InfluxDB, Python, and Go.\n\n - Build reusable automation and internal developer tools that minimize operational toil and cross-team friction\n\n - Develop and extend telemetry, observability and alerting solutions to ensure operational reliability at scale\n\n - Collaborate with Cluster Ops and development teams to identify high-impact automation opportunities and iterate quickly\n\n - Contribute to reliability practices (SLOs, post-mortems, capacity planning)\n\nRequired Experience & Skills\n\n - 2-4+ years in SRE with a strong operations or automation focus\n\n - Production Kubernetes experience\n\n - Solid Python or Go for building tools and automation\n\n - Proficiency with Prometheus, Grafana, and observability-driven workflows\n\n - Ability to measure and communicate impact – reliability metrics, operational toil, velocity gains\n\nNice-to-Have\n\n - Hands-on GitOps expertise, Argo CD / Flux or equivalent, is a plus\n\n - Experience with building continuous delivery pipelines is a strong plus\n\n - Experience with Bazel or similar build systems is a strong plus.\n\n - Familiarity with capacity planning, on-prem or multi-datacenter environments\n\nLocation\n\n - SF Bay Area\n\n - Toronto\n\n \n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"b59048d8-dfdd-4138-86cb-7a2a497cd1ad","title":"3D Physical Design Engineer","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2025-04-10T16:48:26.091+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/b59048d8-dfdd-4138-86cb-7a2a497cd1ad","applyUrl":"https://jobs.ashbyhq.com/cerebras/b59048d8-dfdd-4138-86cb-7a2a497cd1ad/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a member of our tight knit physical design team, you will be working on the design and analysis of 3D integrated products. This role involves a combination of traditional ASIC/SoC physical design skills, packaging, power, clock and cooling analysis. You will work closely with the architecture and RTL team to do R&D on novel concepts for 3D integration.
Skills and Qualifications
Required:
10+ years of physical design/verification experience.
Strong knowledge of block level and full-chip physical verification methodology.
Ideal candidate would be someone who has prior experience in 2.5D/3D/CoWoS integration, physical verification (worked on tools like Alegro for CoWoS/2.5D/3D IC), Si/Pi analysis.
Expert at optimizing for the best power/performance and area.
Experience with the complete physical design flow.
Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.
Expert with IR/EM analysis and resolution.
Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.
Demonstrated ability to work with RTL teams to optimize for physical design.
Knowledge of 2.5D or 3D packaging solutions.
Must have experience with 3d physical design, 3d die stacking, 3d chip design, die-to-die or wafer-to-wafer.
Should demonstrate and raise the bar for ownership, deep dive and should demonstrate strong fundamental understanding of PD concepts.
Preferred:
Experience doing full chip floor planning and integration.
Knowledge of Synopsys tool suite is a plus.
Block PD, sta, IR and pdv is good to have.
Knowledge of clock distribution.
Knowledge of cooling analysis.
The salary range for this position is $150,000 – $270,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a member of our tight knit physical design team, you will be working on the design and analysis of 3D integrated products. This role involves a combination of traditional ASIC/SoC physical design skills, packaging, power, clock and cooling analysis. You will work closely with the architecture and RTL team to do R&D on novel concepts for 3D integration.\n\nSkills and Qualifications\n\nRequired:\n\n - 10+ years of physical design/verification experience.\n\n - Strong knowledge of block level and full-chip physical verification methodology.\n\n - Ideal candidate would be someone who has prior experience in 2.5D/3D/CoWoS integration, physical verification (worked on tools like Alegro for CoWoS/2.5D/3D IC), Si/Pi analysis.\n\n - Expert at optimizing for the best power/performance and area.\n\n - Experience with the complete physical design flow.\n\n - Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.\n\n - Expert with IR/EM analysis and resolution.\n\n - Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.\n\n - Demonstrated ability to work with RTL teams to optimize for physical design.\n\n - Knowledge of 2.5D or 3D packaging solutions.\n\n - Must have experience with 3d physical design, 3d die stacking, 3d chip design, die-to-die or wafer-to-wafer.\n\n - Should demonstrate and raise the bar for ownership, deep dive and should demonstrate strong fundamental understanding of PD concepts.\n\nPreferred:\n\n - Experience doing full chip floor planning and integration.\n\n - Knowledge of Synopsys tool suite is a plus.\n\n - Block PD, sta, IR and pdv is good to have.\n\n - Knowledge of clock distribution.\n\n - Knowledge of cooling analysis.\n\n\n\nThe salary range for this position is $150,000 – $270,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"b5dd4ace-f660-441e-a65e-e599536a7341","title":"Manager, Business Operations","department":"Commercial Operations Departments","team":"Finance","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-04-29T23:30:59.932+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/b5dd4ace-f660-441e-a65e-e599536a7341","applyUrl":"https://jobs.ashbyhq.com/cerebras/b5dd4ace-f660-441e-a65e-e599536a7341/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
This role is a high-leverage seat in that build and a deliberate apprenticeship into operating leadership. You will create the business operations, analytics, and execution system that keeps decision-ready insight flowing as the company scales. You will be embedded with operators, turning messy operational reality into durable processes, clear metrics, and repeatable operating rhythms. You will report to the Head of FP&A and work in close partnership with the COO and operations leadership.
Why now
Cerebras is scaling to meet accelerating demand for fast inference. That growth forces rapid expansion across supply chain, manufacturing, and data center deployment. The company needs closed-loop processes and trusted insight assets that scale with the business and remain durable under increasing scrutiny.
Recent market validation, including a marquee partnership with OpenAI, is an early signal of a broader shift: fast inference is becoming foundational, and it is still early days. Operational excellence will compound, and the systems built now will define how efficiently the company scales.
Role at a glance
Partner with 5 to 10 operational leaders across supply chain, manufacturing, and data center deployment to drive insight and action.
Own and deliver the right information in the right way at the right time. Build the context that allows the organization to know what happened, the implications, and what to do next.
Drive closed-loop operational change. Diagnose bottlenecks, redesign processes, and follow through until adoption and measurable improvement are real.
50/50 analytics and execution. You build the assets (metrics, dashboards, operating packets) and you drive the behaviors (cadence, accountability, decisions).
Apprenticeship into operating leadership. We mean it. The hiring manager has used this model repeatedly over the years and can provide references from alumni who have enjoyed meaningful career acceleration.
Elegant entry point in the cutting edge of AI. If your pace, horsepower, agency, and ambition are elite, this role gives you room to run.. If you make an impact you can chart your own path.
Small, elite, high-standards team. You are a hands-on leader who learns fast, raises the pace, and may selectively add exceptional talent over time to amplify leverage. This will be a small and mighty team.
What you will build
Operational analytics infrastructure required to scale supply chain, manufacturing, inventory management, and data center operations with uncompromising quality and speed.
A decision-quality KPI and reporting architecture: leading indicators, dashboards, recurring reviews, and crisp narratives that operators trust.
Closed-loop mechanisms that turn operational complexity into repeatable processes: metric definitions, data ownership, reconciliation paths, and accountability loops.
System integration between operational data sources and finance systems so that decisions are grounded in consistent, auditable definitions.
Automation and tooling that compounds output, including structured data pulls, workflow automation, and pragmatic use of AI tools to reduce manual work.
Public-company-ready operating rhythms: clean close-to-insight timelines, documented definitions, and durable operating packets that scale with scrutiny.
What you will own
Operations partnering: Work shoulder-to-shoulder with operations leadership to translate operational reality into clear priorities, tradeoffs, and actions.
KPI standards and insight assets: Define the metrics that matter, build the dashboards and operating packets, and keep them accurate as systems and processes evolve.
Operating cadence: Design and run weekly and monthly performance reviews, ensure decisions are made, and close the loop on follow-through.
Process change: Identify the highest-leverage process gaps, drive redesign and adoption, and measure impact in throughput, cycle time, quality, and predictability.
Data quality and reconciliation: Build trust in the numbers by instituting clear definitions, checks, and ownership across operational and finance systems.
Executive communication: Deliver concise narratives that clearly separate signal from noise and drive action.
What success looks like in the first 6 to 12 months
You earn trust. Operators proactively pull you into decisions because your work improves outcomes, not just visibility.
You grow as an operator. You turn consulting-grade problem solving into operating judgment, cross-functional credibility, broader ownership and ultimately IMPACT.
Durable insight assets are live (dashboards, weekly and monthly operating packets, KPI definitions) with a clear cadence and single-source-of-truth inputs.
A small number of critical operational processes are redesigned and adopted, with measurable improvements in speed, predictability, and execution quality.
Cross-functional decisions move faster because the organization shares consistent definitions and a clear view of tradeoffs and constraints.
Manual reporting load declines materially as automation and self-serve assets replace ad hoc requests and one-off analyses.
What we are looking for
We are hiring for horsepower, motor, agency, and systems thinking. Horsepower means exceptional analytical ability. Motor means a high pace of work. Agency means you identify what the business needs next, build it, and bring others along.
6 to 10 years of total experience is a reasonable guide. We will bias toward demonstrated impact and judgment over years.
2+ years at a top-tier strategy consulting firm (McKinsey, BCG, Bain, or similar), with readiness to turn generalist problem-solving into company operating impact.
Experience driving operational change inside a scaling company. This can come from operations, strategy, analytics, or FP&A, as long as you have owned real outcomes.
High learning velocity. You want an apprenticeship, not just a title, and you learn quickly from direct feedback while owning real outcomes.
Strong analytical skills and comfort with imperfect data. You can go from ambiguity to a clear framework, then execute.
High agency. You do not wait for perfect inputs or perfect direction. You move, communicate, and close loops.
Systems thinker. You build infrastructure that continues working when the pace increases and the data gets messy.
Technical fluency beyond spreadsheets (preferred). Comfortable with SQL, Python, or adjacent tooling to pull and shape data and automate recurring work.
Clear executive communication. You distill complexity into concise narratives that drive decisions.
AI affinity. You proactively apply modern tools to speed up workflows, improve quality, and reduce manual work.
Ways to stand out
Experience in hardware, semiconductor, manufacturing, supply chain, or data center operations.
Comfort with Python or similar tooling as evidence of your ability to be a leading creator and user of agents
A track record of building KPI architectures, operating cadences, and repeatable mechanisms from scratch.
Experience partnering directly with COO, C-suite, or VP-level operational leaders.
Demonstrated pattern of high agency: you see problems early and fix them before being asked.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThis role is a high-leverage seat in that build and a deliberate apprenticeship into operating leadership. You will create the business operations, analytics, and execution system that keeps decision-ready insight flowing as the company scales. You will be embedded with operators, turning messy operational reality into durable processes, clear metrics, and repeatable operating rhythms. You will report to the Head of FP&A and work in close partnership with the COO and operations leadership.\n\nWhy now\n\nCerebras is scaling to meet accelerating demand for fast inference. That growth forces rapid expansion across supply chain, manufacturing, and data center deployment. The company needs closed-loop processes and trusted insight assets that scale with the business and remain durable under increasing scrutiny.\n\nRecent market validation, including a marquee partnership with OpenAI, is an early signal of a broader shift: fast inference is becoming foundational, and it is still early days. Operational excellence will compound, and the systems built now will define how efficiently the company scales.\n\nRole at a glance\n\n - Partner with 5 to 10 operational leaders across supply chain, manufacturing, and data center deployment to drive insight and action.\n\n - Own and deliver the right information in the right way at the right time. Build the context that allows the organization to know what happened, the implications, and what to do next.\n\n - Drive closed-loop operational change. Diagnose bottlenecks, redesign processes, and follow through until adoption and measurable improvement are real.\n\n - 50/50 analytics and execution. You build the assets (metrics, dashboards, operating packets) and you drive the behaviors (cadence, accountability, decisions).\n\n - Apprenticeship into operating leadership. We mean it. The hiring manager has used this model repeatedly over the years and can provide references from alumni who have enjoyed meaningful career acceleration.\n\n - Elegant entry point in the cutting edge of AI. If your pace, horsepower, agency, and ambition are elite, this role gives you room to run.. If you make an impact you can chart your own path.\n\n - Small, elite, high-standards team. You are a hands-on leader who learns fast, raises the pace, and may selectively add exceptional talent over time to amplify leverage. This will be a small and mighty team.\n\nWhat you will build\n\n - Operational analytics infrastructure required to scale supply chain, manufacturing, inventory management, and data center operations with uncompromising quality and speed.\n\n - A decision-quality KPI and reporting architecture: leading indicators, dashboards, recurring reviews, and crisp narratives that operators trust.\n\n - Closed-loop mechanisms that turn operational complexity into repeatable processes: metric definitions, data ownership, reconciliation paths, and accountability loops.\n\n - System integration between operational data sources and finance systems so that decisions are grounded in consistent, auditable definitions.\n\n - Automation and tooling that compounds output, including structured data pulls, workflow automation, and pragmatic use of AI tools to reduce manual work.\n\n - Public-company-ready operating rhythms: clean close-to-insight timelines, documented definitions, and durable operating packets that scale with scrutiny.\n\nWhat you will own\n\n - Operations partnering: Work shoulder-to-shoulder with operations leadership to translate operational reality into clear priorities, tradeoffs, and actions.\n\n - KPI standards and insight assets: Define the metrics that matter, build the dashboards and operating packets, and keep them accurate as systems and processes evolve.\n\n - Operating cadence: Design and run weekly and monthly performance reviews, ensure decisions are made, and close the loop on follow-through.\n\n - Process change: Identify the highest-leverage process gaps, drive redesign and adoption, and measure impact in throughput, cycle time, quality, and predictability.\n\n - Data quality and reconciliation: Build trust in the numbers by instituting clear definitions, checks, and ownership across operational and finance systems.\n\n - Executive communication: Deliver concise narratives that clearly separate signal from noise and drive action.\n\nWhat success looks like in the first 6 to 12 months\n\n - You earn trust. Operators proactively pull you into decisions because your work improves outcomes, not just visibility.\n\n - You grow as an operator. You turn consulting-grade problem solving into operating judgment, cross-functional credibility, broader ownership and ultimately IMPACT.\n\n - Durable insight assets are live (dashboards, weekly and monthly operating packets, KPI definitions) with a clear cadence and single-source-of-truth inputs.\n\n - A small number of critical operational processes are redesigned and adopted, with measurable improvements in speed, predictability, and execution quality.\n\n - Cross-functional decisions move faster because the organization shares consistent definitions and a clear view of tradeoffs and constraints.\n\n - Manual reporting load declines materially as automation and self-serve assets replace ad hoc requests and one-off analyses.\n\nWhat we are looking for\n\nWe are hiring for horsepower, motor, agency, and systems thinking. Horsepower means exceptional analytical ability. Motor means a high pace of work. Agency means you identify what the business needs next, build it, and bring others along.\n\n - 6 to 10 years of total experience is a reasonable guide. We will bias toward demonstrated impact and judgment over years.\n\n - 2+ years at a top-tier strategy consulting firm (McKinsey, BCG, Bain, or similar), with readiness to turn generalist problem-solving into company operating impact.\n\n - Experience driving operational change inside a scaling company. This can come from operations, strategy, analytics, or FP&A, as long as you have owned real outcomes.\n\n - High learning velocity. You want an apprenticeship, not just a title, and you learn quickly from direct feedback while owning real outcomes.\n\n - Strong analytical skills and comfort with imperfect data. You can go from ambiguity to a clear framework, then execute.\n\n - High agency. You do not wait for perfect inputs or perfect direction. You move, communicate, and close loops.\n\n - Systems thinker. You build infrastructure that continues working when the pace increases and the data gets messy.\n\n - Technical fluency beyond spreadsheets (preferred). Comfortable with SQL, Python, or adjacent tooling to pull and shape data and automate recurring work.\n\n - Clear executive communication. You distill complexity into concise narratives that drive decisions.\n\n - AI affinity. You proactively apply modern tools to speed up workflows, improve quality, and reduce manual work.\n\nWays to stand out\n\n - Experience in hardware, semiconductor, manufacturing, supply chain, or data center operations.\n\n - Comfort with Python or similar tooling as evidence of your ability to be a leading creator and user of agents\n\n - A track record of building KPI architectures, operating cadences, and repeatable mechanisms from scratch.\n\n - Experience partnering directly with COO, C-suite, or VP-level operational leaders.\n\n - Demonstrated pattern of high agency: you see problems early and fix them before being asked.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"bf35e329-997b-438b-8dab-da21a59a6222","title":"Sr. Technical Staff","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-05-08T19:40:37.861+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/bf35e329-997b-438b-8dab-da21a59a6222","applyUrl":"https://jobs.ashbyhq.com/cerebras/bf35e329-997b-438b-8dab-da21a59a6222/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are seeking a Sr. Technical Staff to support the post-silicon validation of Cerebras Wafer Scale Engines. In this role, you will test and debug new silicon, develop automation and debug tools, support wafer bring-up and manufacturing operations, and collaborate across hardware and software engineering teams to ensure high-quality system performance.
Responsibilities
Perform post-silicon validation of Cerebras Wafer Scale Engines. Test and debug issues on new silicon.
Test, analyze, and characterize high-speed serial interfaces to verify compliance with hardware specifications, record performance data, and recommend design modifications to optimize functionality.
Work with the silicon and operations team to test, bring up, and run burn-in on wafer-scale systems.
Support manufacturing operations to utilize the wafer bring-up flow. Perform wafer bring-ups, diagnose, and debug problems encountered.
Develop and implement hardware to ensure compliance with design specifications.
Collaborate with hardware design engineers and system software engineers to review specifications and recommend changes that will improve the quality and verifiability of the hardware designs.
Create and maintain automated regression test scripts, using Python and/or Bash, that ensure all tests are run and pass after each change to the design, testbench, tests, or reference model.
Work with system team members to diagnose system-related failures. Understand the key system interfaces to FPGAs, power, and cooling, and apply that knowledge to the debug of silicon features.
Develop debug tools in Python to program and analyze the behavior of the Wafer Scale Engine.
Develop wafer bring-up flow utilizing Python and shell scripts to capture the steps required to bring up a wafer in a logical, easy-to-use flow.
Document issues found, tools, and flow.
Skills & Qualifications
Minimum Requirements
Master's degree or foreign equivalent degree in Electrical Engineering, Computer Engineering, or a related field.
Three (3) years of experience as an Application Engineer, Sr. Technical Staff, Hardware Engineer, or a related occupation.
Required Skills
Electrical Signal Integrity Analysis.
Hardware Bring-up & Debug.
Functional and Electrical Characterization.
Test automation using scripting language.
High-Speed Interfaces & Protocols, including Ethernet, CPRI, or Interlaken.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are seeking a Sr. Technical Staff to support the post-silicon validation of Cerebras Wafer Scale Engines. In this role, you will test and debug new silicon, develop automation and debug tools, support wafer bring-up and manufacturing operations, and collaborate across hardware and software engineering teams to ensure high-quality system performance.\n\nResponsibilities\n\n - Perform post-silicon validation of Cerebras Wafer Scale Engines. Test and debug issues on new silicon.\n\n - Test, analyze, and characterize high-speed serial interfaces to verify compliance with hardware specifications, record performance data, and recommend design modifications to optimize functionality.\n\n - Work with the silicon and operations team to test, bring up, and run burn-in on wafer-scale systems.\n\n - Support manufacturing operations to utilize the wafer bring-up flow. Perform wafer bring-ups, diagnose, and debug problems encountered.\n\n - Develop and implement hardware to ensure compliance with design specifications.\n\n - Collaborate with hardware design engineers and system software engineers to review specifications and recommend changes that will improve the quality and verifiability of the hardware designs.\n\n - Create and maintain automated regression test scripts, using Python and/or Bash, that ensure all tests are run and pass after each change to the design, testbench, tests, or reference model.\n\n - Work with system team members to diagnose system-related failures. Understand the key system interfaces to FPGAs, power, and cooling, and apply that knowledge to the debug of silicon features.\n\n - Develop debug tools in Python to program and analyze the behavior of the Wafer Scale Engine.\n\n - Develop wafer bring-up flow utilizing Python and shell scripts to capture the steps required to bring up a wafer in a logical, easy-to-use flow.\n\n - Document issues found, tools, and flow.\n\nSkills & Qualifications\n\nMinimum Requirements\n\n - Master's degree or foreign equivalent degree in Electrical Engineering, Computer Engineering, or a related field.\n\n - Three (3) years of experience as an Application Engineer, Sr. Technical Staff, Hardware Engineer, or a related occupation.\n\n - Required Skills\n\n - Electrical Signal Integrity Analysis.\n\n - Hardware Bring-up & Debug.\n\n - Functional and Electrical Characterization.\n\n - Test automation using scripting language.\n\n - High-Speed Interfaces & Protocols, including Ethernet, CPRI, or Interlaken.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"c2d428d4-b32d-46e8-ae5d-37fe54fb9bf7","title":"Regional Data Center Manager - Western Canada","department":"Hardware Departments","team":"Datacenters","employmentType":"FullTime","location":"Western Office","secondaryLocations":[],"publishedAt":"2026-06-29T19:01:00.641+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"British Columbia","addressCountry":"Canada","addressLocality":"Vancouver"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/c2d428d4-b32d-46e8-ae5d-37fe54fb9bf7","applyUrl":"https://jobs.ashbyhq.com/cerebras/c2d428d4-b32d-46e8-ae5d-37fe54fb9bf7/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Regional Data Center Manager – Western Canada
Location
Calgary, Edmonton or Vancouver, BC (regional travel required).
About The Role
Cerebras Systems is seeking a Regional Data Center Manager to lead infrastructure operations and deployment execution across Western Canada.
This role is responsible for ensuring that AI infrastructure is delivered, operated, and scaled effectively, while maintaining strong alignment with global engineering and operations teams.
This is a field-oriented leadership role requiring:
Hands-on data center experience.
Solid understanding of MEP systems.
Direct engagement with facility providers.
The ability to manage local teams while executing HQ-driven requirements.
Lead day-to-day operations across Western Canada sites.
Ensure infrastructure meets uptime, performance, and reliability targets.
Own incident response coordination for facility-related issues.
Maintain alignment with global:
Cluster Operations;
Network Operations;
Platform Engineering.
Act as primary interface with facility operators and vendors.
Ensure site infrastructure supports:
High-density compute loads;
Liquid cooling systems;
Redundant power architectures;
Validate facility performance against defined operational thresholds.
Execute modular deployments (5MW increments).
Lead coordination of:
Site readiness;
Equipment install;
Commissioning and operational handoff.
Support scaling toward multi-site, high-capacity regional footprint.
Lead and develop local data center technicians and engineers.
Ensure execution aligns with HQ-defined standards, procedures, and timelines.
Serve as the operational bridge between HQ and field teams.
Required
5–10+ years of data center or critical facility experience.
Working knowledge of MEP systems (mechanical, electrical, plumbing).
Experience interfacing with facility providers and vendors.
Demonstrated ability to lead site-level teams.
Ability to execute both operationally and managerially in a fast-paced environment.
Preferred
Experience with AI/HPC infrastructure.
Exposure to liquid cooling systems.
Experience operating in cold-weather environments.
Familiarity with structured incident management frameworks.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nRegional Data Center Manager – Western Canada\n\nLocation\nCalgary, Edmonton or Vancouver, BC (regional travel required).\n\n\nAbout The Role\nCerebras Systems is seeking a Regional Data Center Manager to lead infrastructure operations and deployment execution across Western Canada.\n\n\nThis role is responsible for ensuring that AI infrastructure is delivered, operated, and scaled effectively, while maintaining strong alignment with global engineering and operations teams.\n\n\nThis is a field-oriented leadership role requiring:\n\n - Hands-on data center experience.\n\n - Solid understanding of MEP systems.\n\n - Direct engagement with facility providers.\n\n - The ability to manage local teams while executing HQ-driven requirements.\n \n\n\nKEY RESPONSIBILITIES\nREGIONAL OPERATIONS OWNERSHIP\n\n - Lead day-to-day operations across Western Canada sites.\n\n - Ensure infrastructure meets uptime, performance, and reliability targets.\n\n - Own incident response coordination for facility-related issues.\n\n - Maintain alignment with global:\n \n - Cluster Operations;\n \n - Network Operations;\n \n - Platform Engineering.\n\n\nFACILITY INTERFACE & INFRASTRUCTURE OVERSIGHT\n\n - Act as primary interface with facility operators and vendors.\n\n - Ensure site infrastructure supports:\n \n - High-density compute loads;\n \n - Liquid cooling systems;\n \n - Redundant power architectures;\n \n - Validate facility performance against defined operational thresholds.\n\n\nDEPLOYMENT & BUILD EXECUTION\n\n - Execute modular deployments (5MW increments).\n\n - Lead coordination of:\n \n - Site readiness;\n \n - Equipment install;\n \n - Commissioning and operational handoff.\n\n - Support scaling toward multi-site, high-capacity regional footprint.\n\n\nTEAM LEADERSHIP & HQ ALIGNMENT\n\n - Lead and develop local data center technicians and engineers.\n\n - Ensure execution aligns with HQ-defined standards, procedures, and timelines.\n\n - Serve as the operational bridge between HQ and field teams.\n\n\nQUALIFICATIONS\n\nRequired\n\n - 5–10+ years of data center or critical facility experience.\n\n - Working knowledge of MEP systems (mechanical, electrical, plumbing).\n\n - Experience interfacing with facility providers and vendors.\n\n - Demonstrated ability to lead site-level teams.\n\n - Ability to execute both operationally and managerially in a fast-paced environment.\n\nPreferred\n\n - Experience with AI/HPC infrastructure.\n\n - Exposure to liquid cooling systems.\n\n - Experience operating in cold-weather environments.\n\n - Familiarity with structured incident management frameworks.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"c3890fd4-99de-4a22-b442-b6a77a717dfb","title":"Full Stack LLM Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"Toronto Office","secondaryLocations":[],"publishedAt":"2025-07-18T20:38:09.402+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/c3890fd4-99de-4a22-b442-b6a77a717dfb","applyUrl":"https://jobs.ashbyhq.com/cerebras/c3890fd4-99de-4a22-b442-b6a77a717dfb/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are seeking a versatile and experienced engineer to join our Inference Core Model Bringup team. This team is responsible to rapidly bring up state-of-the-art open-source models (like LLaMA, Qwen, etc) or customer-provided proprietary models on our Cerebras CSX systems. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire Cerebras software stack.
Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.
Responsibilities
Contribute to the end-to-end bring up of ML models on Cerebras CSX systems.
Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.
Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization.
Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups.
Skills & Qualifications
Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field.
Comfort navigating the full AI toolchain: Python modeling code, compiler IRs, performance profiling, etc.
Strong debugging skills across performance, numerical accuracy, and runtime integration.
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion).
Proficiency in C/C++ programming and experience with low-level optimization.
Proven experience in compiler development, particularly with LLVM and/or MLIR.
Strong background in optimization techniques, particularly those involving NP-hard problems.
What We Offer
Competitive salary and benefits package.
Opportunities for professional growth and career advancement.
A dynamic and innovative work environment.
The chance to work on cutting-edge technologies and make a significant impact on the future of AI.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\nWe are seeking a versatile and experienced engineer to join our Inference Core Model Bringup team. This team is responsible to rapidly bring up state-of-the-art open-source models (like LLaMA, Qwen, etc) or customer-provided proprietary models on our Cerebras CSX systems. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire Cerebras software stack.\nYour work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications.\n\nResponsibilities\n\n - Contribute to the end-to-end bring up of ML models on Cerebras CSX systems.\n\n - Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning.\n\n - Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization.\n\n - Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups.\n\nSkills & Qualifications\n\n - Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field.\n\n - Comfort navigating the full AI toolchain: Python modeling code, compiler IRs, performance profiling, etc.\n\n - Strong debugging skills across performance, numerical accuracy, and runtime integration.\n\n - Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion).\n\n - Proficiency in C/C++ programming and experience with low-level optimization.\n\n - Proven experience in compiler development, particularly with LLVM and/or MLIR.\n\n - Strong background in optimization techniques, particularly those involving NP-hard problems.\n\nWhat We Offer\n\n - Competitive salary and benefits package.\n\n - Opportunities for professional growth and career advancement.\n\n - A dynamic and innovative work environment.\n\n - The chance to work on cutting-edge technologies and make a significant impact on the future of AI.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"c8fbf33e-a200-483f-8980-673a0a7dab53","title":"Mechanical Engineer - Datacenter Deliver","department":"Hardware Departments","team":"Datacenters","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-07-10T22:42:54.861+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/c8fbf33e-a200-483f-8980-673a0a7dab53","applyUrl":"https://jobs.ashbyhq.com/cerebras/c8fbf33e-a200-483f-8980-673a0a7dab53/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Role
We are seeking an experienced Mechanical Engineer to join the Data Center Delivery organization. This role will be responsible for technical oversight of mechanical infrastructure across leased AI data center deployments, ensuring facilities are designed, constructed, commissioned, and handed over to meet Cerebras' performance, reliability, scalability, and schedule requirements.
The Mechanical Engineer will serve as the owner's technical representative, partnering closely with colocation providers, developers, EPC contractors, OEMs, and internal infrastructure teams to deliver world-class AI computing facilities.
Unlike traditional data center development roles, this position focuses on technical governance, design reviews, owner acceptance, fit-out integration, and operational readiness rather than performing detailed engineering design.
Responsibilities
Serve as the subject matter expert for mechanical infrastructure across assigned projects.
Review and approve basis of design, drawings, equipment submittals, RFIs, and change requests.
Ensure compliance with Cerebras engineering standards.
Validate cooling architectures supporting high-density AI deployments.
White Space Delivery
Provide technical oversight for in-row/rear-door cooling systems
Coolant Distribution Units (CDUs)
Thermal expansion tanks
Buffer tanks
Stainless steel piping
Hot aisle containment
Mechanical supports
Leak detection systems
CRAH/CRAC integration
Water treatment systems
White space mechanical distribution
Colocation & Developer Management
Act as owner's representative during design, construction, and commissioning.
Review developer design decisions.
Participate in design workshops.
Resolve technical issues.
Evaluate value engineering proposals.
Ensure contracted mechanical scope is delivered.
Construction Support
Perform regular site inspections.
Monitor installation quality.
Review contractor installation methods.
Support schedule recovery planning.
Validate installations against approved drawings.
Participate in turnover inspections.
Commissioning
Support FAT, SAT, IST, FPT, mechanical startup, cooling optimization, and owner acceptance.
Review commissioning documentation and verify system performance prior to turnover.
Operational Readiness
Ensure complete O&M documentation.
Develop spare parts strategy.
Support maintenance procedures.
Verify asset documentation.
Coordinate training packages.
Manage mechanical warranties.
Cross Functional Collaboration
Work with Electrical Engineering, Network Engineering, Construction TPMs, Commissioning Managers, Capacity Planning, Operations, Procurement, colocation providers, and OEMs.
Skills & Qualifications
Required
Bachelor's degree in Mechanical Engineering.
8+ years in mission-critical facilities or hyperscale data centers.
Strong understanding of chilled water cooling systems.
Experience with high-density AI/HPC cooling.
Knowledge of data center cooling infrastructure.
Construction and commissioning experience.
Ability to interpret mechanical drawings.
Excellent communication and project management skills.
Preferred
PE license preferred.
Experience supporting leased data centers, hyperscale or AI data centers
Familiarity with liquid cooling.
Knowledge of ASHRAE thermal guidelines.
Experience with BIM/Revit/Navisworks.
Familiarity with CFD analysis.
Technical Expertise
Chilled water systems
Cooling towers
Heat exchangers
CDUs
Pumping systems
Buffer tanks
Expansion tanks
Stainless steel piping
Glycol systems
Water treatment
Hot aisle containment
High-density cooling
Leak detection
BMS integration
Mechanical commissioning
Root cause analysis
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nThe Role\n\nWe are seeking an experienced Mechanical Engineer to join the Data Center Delivery organization. This role will be responsible for technical oversight of mechanical infrastructure across leased AI data center deployments, ensuring facilities are designed, constructed, commissioned, and handed over to meet Cerebras' performance, reliability, scalability, and schedule requirements.\n\nThe Mechanical Engineer will serve as the owner's technical representative, partnering closely with colocation providers, developers, EPC contractors, OEMs, and internal infrastructure teams to deliver world-class AI computing facilities.\n\nUnlike traditional data center development roles, this position focuses on technical governance, design reviews, owner acceptance, fit-out integration, and operational readiness rather than performing detailed engineering design.\n\nResponsibilities\n\n - Serve as the subject matter expert for mechanical infrastructure across assigned projects.\n\n - Review and approve basis of design, drawings, equipment submittals, RFIs, and change requests.\n\n - Ensure compliance with Cerebras engineering standards.\n\n - Validate cooling architectures supporting high-density AI deployments.\n\nWhite Space Delivery\n\n - Provide technical oversight for in-row/rear-door cooling systems\n\n - Coolant Distribution Units (CDUs)\n\n - Thermal expansion tanks\n\n - Buffer tanks\n\n - Stainless steel piping\n\n - Hot aisle containment\n\n - Mechanical supports\n\n - Leak detection systems\n\n - CRAH/CRAC integration\n\n - Water treatment systems\n\n - White space mechanical distribution\n\nColocation & Developer Management\n\n - Act as owner's representative during design, construction, and commissioning.\n\n - Review developer design decisions.\n\n - Participate in design workshops.\n\n - Resolve technical issues.\n\n - Evaluate value engineering proposals.\n\n - Ensure contracted mechanical scope is delivered.\n\nConstruction Support\n\n - Perform regular site inspections.\n\n - Monitor installation quality.\n\n - Review contractor installation methods.\n\n - Support schedule recovery planning.\n\n - Validate installations against approved drawings.\n\n - Participate in turnover inspections.\n\nCommissioning\n\n - Support FAT, SAT, IST, FPT, mechanical startup, cooling optimization, and owner acceptance.\n\n - Review commissioning documentation and verify system performance prior to turnover.\n\nOperational Readiness\n\n - Ensure complete O&M documentation.\n\n - Develop spare parts strategy.\n\n - Support maintenance procedures.\n\n - Verify asset documentation.\n\n - Coordinate training packages.\n\n - Manage mechanical warranties.\n\nCross Functional Collaboration\n\n - Work with Electrical Engineering, Network Engineering, Construction TPMs, Commissioning Managers, Capacity Planning, Operations, Procurement, colocation providers, and OEMs.\n\n\n\nSkills & Qualifications\n\nRequired\n\n - Bachelor's degree in Mechanical Engineering.\n\n - 8+ years in mission-critical facilities or hyperscale data centers.\n\n - Strong understanding of chilled water cooling systems.\n\n - Experience with high-density AI/HPC cooling.\n\n - Knowledge of data center cooling infrastructure.\n\n - Construction and commissioning experience.\n\n - Ability to interpret mechanical drawings.\n\n - Excellent communication and project management skills.\n\nPreferred\n\n - PE license preferred.\n\n - Experience supporting leased data centers, hyperscale or AI data centers\n\n - Familiarity with liquid cooling.\n\n - Knowledge of ASHRAE thermal guidelines.\n\n - Experience with BIM/Revit/Navisworks.\n\n - Familiarity with CFD analysis.\n\nTechnical Expertise\n\n - Chilled water systems\n\n - Cooling towers\n\n - Heat exchangers\n\n - CDUs\n\n - Pumping systems\n\n - Buffer tanks\n\n - Expansion tanks\n\n - Stainless steel piping\n\n - Glycol systems\n\n - Water treatment\n\n - Hot aisle containment\n\n - High-density cooling\n\n - Leak detection\n\n - BMS integration\n\n - Mechanical commissioning\n\n - Root cause analysis\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"cf45f13c-b6a9-4df2-b6c3-eefea14a024f","title":"Inference ML API SDET","department":"Software","team":"Cloud","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[{"location":"Toronto Office","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-06-29T15:37:31.221+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/cf45f13c-b6a9-4df2-b6c3-eefea14a024f","applyUrl":"https://jobs.ashbyhq.com/cerebras/cf45f13c-b6a9-4df2-b6c3-eefea14a024f/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Team
The ML API Quality team is responsible for the confidence behind every production release shipped to Cerebras Inference Cloud. We work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.
We are scaling quickly. The systems are growing in complexity, traffic is increasing rapidly, and release velocity remains high. We need engineers who can build quality systems that scale with the business.
About The Role
As a Senior Software Engineer in Test for the ML API features team, you will lead testing strategy and execution for AI/ML models, evaluating accuracy, fairness, and performance at scale. You will serve as a key technical leader in delivering and validating all software and hardware components for Cerebras API Features. You will own software components feature integration quality and drive pre-deployment and production validation for Cerebras inference solutions. In this role, you will define and champion best testing practices, establish robust debugging methodologies, and mentor junior engineers while advocating for world-class product quality.
Responsibilities
Architect and own end-to-end test strategies for new features, developing scalable tests, frameworks, and tooling to ensure quality.
Lead contributions to industry-standard benchmarks and drive adoption of rigorous evaluation methodologies.
Define and drive automation initiatives to significantly improve internal engineering efficiency and test coverage.
Make strategic decisions around coverage trade-offs, resource requirements, and risk-based testing priorities.
Serve as a technical anchor in a highly agile environment, adapting quickly to shifting priorities while maintaining quality standards.
Mentor and guide junior SDETs on testing methodology, debugging practices, and automation development.
Proactively identify systemic quality gaps and drive cross-functional initiatives to address them.
Lead and facilitate effective technical communication across teams and time zones.
Skills & Qualifications
5+ years of relevant industry experience in software integration, development, or quality engineering.
Deep expertise in automation and programming using one or more languages such as Python, C++, or Go; ability to design and build reusable test frameworks from the ground up.
Proven experience testing compute, machine learning, networking, or storage systems within large-scale enterprise environments.
Strong track record of debugging complex issues across distributed, scaled-out deployments.
Demonstrated ability to lead cross-functional quality initiatives involving product development, product management, customer operations, and field teams.
Excellent verbal and written communication skills, with experience presenting technical findings to both engineering and leadership audiences.
Strong organizational skills, ownership mindset, and ability to drive projects to completion independently.
Experience leading and mentoring engineers across geographically dispersed teams and time zones.
Preferred Skills & Qualifications
Hands-on experience with ML workloads including LLM and/or multimodal training or inference.
Deep familiarity with hardware architecture, performance optimizations, compilers, and ML frameworks.
Experience designing test strategies for distributed systems, cloud infrastructure, and security validation.
Experience with microservices deployment, debugging, and orchestration at scale.
Prior experience owning or significantly contributing to a team's quality engineering culture or test infrastructure.
Location
This role follows a hybrid schedule, requiring in-office presence 3 days per week. Fully remote is not an option.
Office locations: Sunnyvale, CA | Toronto, Canada
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Team\n\nThe ML API Quality team is responsible for the confidence behind every production release shipped to Cerebras Inference Cloud. We work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.\n\nWe are scaling quickly. The systems are growing in complexity, traffic is increasing rapidly, and release velocity remains high. We need engineers who can build quality systems that scale with the business.\n\nAbout The Role\n\nAs a Senior Software Engineer in Test for the ML API features team, you will lead testing strategy and execution for AI/ML models, evaluating accuracy, fairness, and performance at scale. You will serve as a key technical leader in delivering and validating all software and hardware components for Cerebras API Features. You will own software components feature integration quality and drive pre-deployment and production validation for Cerebras inference solutions. In this role, you will define and champion best testing practices, establish robust debugging methodologies, and mentor junior engineers while advocating for world-class product quality.\n\nResponsibilities\n\n - Architect and own end-to-end test strategies for new features, developing scalable tests, frameworks, and tooling to ensure quality.\n\n - Lead contributions to industry-standard benchmarks and drive adoption of rigorous evaluation methodologies.\n\n - Define and drive automation initiatives to significantly improve internal engineering efficiency and test coverage.\n\n - Make strategic decisions around coverage trade-offs, resource requirements, and risk-based testing priorities.\n\n - Serve as a technical anchor in a highly agile environment, adapting quickly to shifting priorities while maintaining quality standards.\n\n - Mentor and guide junior SDETs on testing methodology, debugging practices, and automation development.\n\n - Proactively identify systemic quality gaps and drive cross-functional initiatives to address them.\n\n - Lead and facilitate effective technical communication across teams and time zones.\n\nSkills & Qualifications\n\n - 5+ years of relevant industry experience in software integration, development, or quality engineering.\n\n - Deep expertise in automation and programming using one or more languages such as Python, C++, or Go; ability to design and build reusable test frameworks from the ground up.\n\n - Proven experience testing compute, machine learning, networking, or storage systems within large-scale enterprise environments.\n\n - Strong track record of debugging complex issues across distributed, scaled-out deployments.\n\n - Demonstrated ability to lead cross-functional quality initiatives involving product development, product management, customer operations, and field teams.\n\n - Excellent verbal and written communication skills, with experience presenting technical findings to both engineering and leadership audiences.\n\n - Strong organizational skills, ownership mindset, and ability to drive projects to completion independently.\n\n - Experience leading and mentoring engineers across geographically dispersed teams and time zones.\n\nPreferred Skills & Qualifications\n\n - Hands-on experience with ML workloads including LLM and/or multimodal training or inference.\n\n - Deep familiarity with hardware architecture, performance optimizations, compilers, and ML frameworks.\n\n - Experience designing test strategies for distributed systems, cloud infrastructure, and security validation.\n\n - Experience with microservices deployment, debugging, and orchestration at scale.\n\n - Prior experience owning or significantly contributing to a team's quality engineering culture or test infrastructure.\n\nLocation\n\nThis role follows a hybrid schedule, requiring in-office presence 3 days per week. Fully remote is not an option.\n\nOffice locations: Sunnyvale, CA | Toronto, Canada\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"cfe7a6e6-110a-45ea-aad2-8e9e3bbf4814","title":"Distributed Software Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-01-09T20:29:55.470+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/cfe7a6e6-110a-45ea-aad2-8e9e3bbf4814","applyUrl":"https://jobs.ashbyhq.com/cerebras/cfe7a6e6-110a-45ea-aad2-8e9e3bbf4814/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras Systems is a pioneer in large-scale AI Supercomputers. These multi-exaflop supercomputers are deployed in some of the biggest datacenters. These supercomputers are built using our Wafer-Scale Cluster technology - a cluster of several Wafer Scale Engine (WSE) chips. The Cluster engineering team is responsible for delivering software that are all-things related to cluster.
Automate bare-metal configuration of networking, OS, and application software in large clusters of Cerebras WSE, servers, and switches.
Additional push button workflows for cluster upgrades, downgrades, and security patching with key metrics to minimize downtime on clusters.
An orchestration and scheduler system for resource allocation, job submission C placements for a multi-user environment on a cluster.
Seamless support for both on-premise and cloud mode deployment and operations.
A robust system for monitoring, detecting and handling failures for a variety of resources on the clusters (including High Availability of clusters).
Broad cluster and job monitoring and visualization capabilities, along with alerting systems.
User facing tools to monitor the status of jobs and collect metrics.
Administrator facing tools to manage and operate large clusters.
Strong track record of software architecture, system design and development.
Strong track record of development in distributed cluster.
Strong understanding of Kubernetes (K8s) software ecosystem, Prometheus and Grafana.
Strong development skills in GoLang, Python, bash.
Strong debugging skills with distributed systems.
Strong skill to develop tests for the new features and regress old features.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nCerebras Systems is a pioneer in large-scale AI Supercomputers. These multi-exaflop supercomputers are deployed in some of the biggest datacenters. These supercomputers are built using our Wafer-Scale Cluster technology - a cluster of several Wafer Scale Engine (WSE) chips. The Cluster engineering team is responsible for delivering software that are all-things related to cluster.\n\n\nRESPONSIBILITIES\n\n - Automate bare-metal configuration of networking, OS, and application software in large clusters of Cerebras WSE, servers, and switches.\n\n - Additional push button workflows for cluster upgrades, downgrades, and security patching with key metrics to minimize downtime on clusters.\n\n - An orchestration and scheduler system for resource allocation, job submission C placements for a multi-user environment on a cluster.\n\n - Seamless support for both on-premise and cloud mode deployment and operations.\n\n - A robust system for monitoring, detecting and handling failures for a variety of resources on the clusters (including High Availability of clusters).\n\n - Broad cluster and job monitoring and visualization capabilities, along with alerting systems.\n\n - User facing tools to monitor the status of jobs and collect metrics.\n\n - Administrator facing tools to manage and operate large clusters.\n\n\nSKILLS & QUALIFICATIONS\n\n - Strong track record of software architecture, system design and development.\n\n - Strong track record of development in distributed cluster.\n\n - Strong understanding of Kubernetes (K8s) software ecosystem, Prometheus and Grafana.\n\n - Strong development skills in GoLang, Python, bash.\n\n - Strong debugging skills with distributed systems.\n\n - Strong skill to develop tests for the new features and regress old features.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d0baac54-76cb-4e8d-93bd-24e121113870","title":"Physical Design Engineer","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-06-10T15:46:29.974+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d0baac54-76cb-4e8d-93bd-24e121113870","applyUrl":"https://jobs.ashbyhq.com/cerebras/d0baac54-76cb-4e8d-93bd-24e121113870/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a member of our tight knit physical design team, you will be working on the design and analysis of 3D integrated products. This role involves a combination of traditional ASIC/SoC physical design skills, packaging, power, clock and cooling analysis. You will work closely with the architecture and RTL team to do R&D on novel concepts for 3D integration.
Skills and Qualifications
Required:
10+ years of physical design/verification experience.
Strong knowledge of block level and full-chip physical verification methodology.
Strong background in block physical design, Synthesis, PDV and IR.
Expert at optimizing for the best power/performance and area.
Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.
Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.
Expert with IR/EM analysis and resolution.
Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.
Demonstrated ability to work with RTL teams to optimize for physical design.
Should demonstrate ownership, deep dive and should demonstrate strong fundamental understanding of PD concepts.
Knowledge of 2.5D or 3D packaging solutions.
Preferred:
Experience doing full chip floor planning and integration.
Knowledge of clock distribution.
Knowledge of cooling analysis.
STA would be good to have.
The salary range for this position is $230,000 – $280,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a member of our tight knit physical design team, you will be working on the design and analysis of 3D integrated products. This role involves a combination of traditional ASIC/SoC physical design skills, packaging, power, clock and cooling analysis. You will work closely with the architecture and RTL team to do R&D on novel concepts for 3D integration.\n\nSkills and Qualifications\n\nRequired:\n\n - 10+ years of physical design/verification experience.\n\n - Strong knowledge of block level and full-chip physical verification methodology.\n\n - Strong background in block physical design, Synthesis, PDV and IR.\n\n - Expert at optimizing for the best power/performance and area.\n\n - Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.\n\n - Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.\n\n - Expert with IR/EM analysis and resolution.\n\n - Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.\n\n - Demonstrated ability to work with RTL teams to optimize for physical design.\n\n - Should demonstrate ownership, deep dive and should demonstrate strong fundamental understanding of PD concepts.\n\n - Knowledge of 2.5D or 3D packaging solutions.\n\n\n\nPreferred:\n\n - Experience doing full chip floor planning and integration.\n\n - Knowledge of clock distribution.\n\n - Knowledge of cooling analysis.\n\n - STA would be good to have.\n\n\n\nThe salary range for this position is $230,000 – $280,000 annually. Actual compensation will be determined based on factors such as experience, skills, qualifications, and location.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d418c1b5-1968-452b-89d0-4d3fa566265e","title":"Physical Design Engineer","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-05-06T02:25:08.663+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d418c1b5-1968-452b-89d0-4d3fa566265e","applyUrl":"https://jobs.ashbyhq.com/cerebras/d418c1b5-1968-452b-89d0-4d3fa566265e/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As our team grows Cerebras is looking for a world class physical design engineer. We are looking for a strong learner who can learn how we do PD and integration of our wafer scale design.
As a member of our tight knit physical design team, you will perform a variety of physical design tasks such as synthesis, place and route, timing and block closure / sign off. You will be involved in all aspects of physical design and implementation. You will work closely with the RTL team and with full-chip integration of these blocks.
Skills and Qualifications:
7+ years of physical design/verification experience.
Strong experience in block/subsystem timing closure.
Strong ability to learn and grow with the team.
Strong knowledge of block level and full-chip physical verification methodology.
Expert at optimizing for the best power/performance and area.
Experience with block physical design, PDV and IR.
Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.
Expert with IR/EM analysis and resolution.
Good understanding of full chip floor-planning and integration.
Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.
Demonstrated ability to work with RTL teams to optimize for physical design.
Ability to take on a leadership role after ramping up on wafer scale design.
Should demonstrate learn and be curious, good fundamental understanding of PD concepts and should be coachable.
BSEE, MSEE, PH.D EE preferred.
Preferred:
Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.
Synthesis and STA would be good to have.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs our team grows Cerebras is looking for a world class physical design engineer. We are looking for a strong learner who can learn how we do PD and integration of our wafer scale design.\nAs a member of our tight knit physical design team, you will perform a variety of physical design tasks such as synthesis, place and route, timing and block closure / sign off. You will be involved in all aspects of physical design and implementation. You will work closely with the RTL team and with full-chip integration of these blocks.\n\nSkills and Qualifications:\n\n - 7+ years of physical design/verification experience.\n\n - Strong experience in block/subsystem timing closure.\n\n - Strong ability to learn and grow with the team.\n\n - Strong knowledge of block level and full-chip physical verification methodology.\n\n - Expert at optimizing for the best power/performance and area.\n\n - Experience with block physical design, PDV and IR.\n\n - Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.\n\n - Expert with IR/EM analysis and resolution.\n\n - Good understanding of full chip floor-planning and integration.\n\n - Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.\n\n - Demonstrated ability to work with RTL teams to optimize for physical design.\n\n - Ability to take on a leadership role after ramping up on wafer scale design.\n\n - Should demonstrate learn and be curious, good fundamental understanding of PD concepts and should be coachable.\n\n - BSEE, MSEE, PH.D EE preferred.\n\nPreferred:\n\n - Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.\n\n - Synthesis and STA would be good to have.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d4a6507d-8908-4ea5-ac3a-0815533e2512","title":"Network Architect","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2025-11-13T15:28:07.028+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d4a6507d-8908-4ea5-ac3a-0815533e2512","applyUrl":"https://jobs.ashbyhq.com/cerebras/d4a6507d-8908-4ea5-ac3a-0815533e2512/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Network Architect on the Cluster Architecture Team, you will work closely with the vendors, internal networking teams and industry peers to develop best-in-class front-end datacenter and interconnect architecture of the current and future generations of the Cerebras AI clusters. You will be responsible for developing proof-of-concept of new network designs and features enabling resilient and reliable network for AI workloads. The role will require cross-functional collaboration and interaction with diverse hardware components (e.g., network devices and the Wafer-Scale Engine) as well as software at several layers of the stack, from host-side networking to cluster-level coordination. The role also requires understanding of network monitoring systems and network debugging methodologies.
Responsibilities
Design and architect front-end network fabrics for AI/ML and HPC systems.
Identify and resolve performance and efficiency bottlenecks, ensuring high resource utilization, low latency, and high-throughput communication.
Lead cross-functional technical projects spanning multiple teams and integrating diverse software and hardware components to deliver advanced networking technologies.
Foster clear and effective communication across teams and stakeholders.
Collaborate with vendors and industry partners to shape network hardware and feature roadmaps.
Represent Cerebras in industry forums and technical communities.
Serve as the central point of contact for network reliability issues.
Skills & Qualifications
Ph.D. in Computer Science or Electrical Engineering + 10 years industry experience or Master’s in CS or EE + 15 years industry experience.
8+ Years of experience in large scale network designs in datacenter and cloud environments.
Extensive experience debugging networking issues in large distributed systems environment with multiple networking platforms and protocols.
Experience of managing and leading multi-phase and multi-team projects.
Networking platforms like Juniper, Arista, Cisco, Open box architectures (Sonic, FOBSS).
Networking protocols like VXLAN, EVPN, RoCE, BGP, DCQCN, PFC, Streaming telemetry.
Familiarity with automation languages like Python, or Go.
Familiarity with Network visibility and management systems.
Prior experience in hyperscalers or cloud service providers is strongly preferred.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs a Network Architect on the Cluster Architecture Team, you will work closely with the vendors, internal networking teams and industry peers to develop best-in-class front-end datacenter and interconnect architecture of the current and future generations of the Cerebras AI clusters. You will be responsible for developing proof-of-concept of new network designs and features enabling resilient and reliable network for AI workloads. The role will require cross-functional collaboration and interaction with diverse hardware components (e.g., network devices and the Wafer-Scale Engine) as well as software at several layers of the stack, from host-side networking to cluster-level coordination. The role also requires understanding of network monitoring systems and network debugging methodologies.\n\nResponsibilities\n\n - Design and architect front-end network fabrics for AI/ML and HPC systems.\n\n - Identify and resolve performance and efficiency bottlenecks, ensuring high resource utilization, low latency, and high-throughput communication.\n\n - Lead cross-functional technical projects spanning multiple teams and integrating diverse software and hardware components to deliver advanced networking technologies.\n\n - Foster clear and effective communication across teams and stakeholders.\n\n - Collaborate with vendors and industry partners to shape network hardware and feature roadmaps.\n\n - Represent Cerebras in industry forums and technical communities.\n\n - Serve as the central point of contact for network reliability issues.\n\nSkills & Qualifications\n\n - Ph.D. in Computer Science or Electrical Engineering + 10 years industry experience or Master’s in CS or EE + 15 years industry experience.\n\n - 8+ Years of experience in large scale network designs in datacenter and cloud environments.\n\n - Extensive experience debugging networking issues in large distributed systems environment with multiple networking platforms and protocols.\n\n - Experience of managing and leading multi-phase and multi-team projects.\n\n - Networking platforms like Juniper, Arista, Cisco, Open box architectures (Sonic, FOBSS).\n\n - Networking protocols like VXLAN, EVPN, RoCE, BGP, DCQCN, PFC, Streaming telemetry.\n\n - Familiarity with automation languages like Python, or Go.\n\n - Familiarity with Network visibility and management systems.\n\n - Prior experience in hyperscalers or cloud service providers is strongly preferred.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d654a704-2c58-4ba6-9109-2c92aecb2503","title":"Applied Machine Learning Research Scientist","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-03-05T22:03:05.014+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/d654a704-2c58-4ba6-9109-2c92aecb2503","applyUrl":"https://jobs.ashbyhq.com/cerebras/d654a704-2c58-4ba6-9109-2c92aecb2503/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As an Applied Machine Learning Research Scientist at Cerebras, you will play a key role in turning modern machine learning techniques into scalable, high-performance systems. This role sits at the intersection of modeling and systems focused not on publishing new algorithms, but on understanding how they work and making them run effectively at scale. Your work will directly impact how large language models (LLMs) are trained, optimized, and deployed on one of the most advanced AI platforms in the world.
You will work closely with researchers and senior engineers to implement and improve workflows for LLM pretraining, fine-tuning, and reinforcement learning-based post-training. This includes building training pipelines, debugging complex system behaviors, improving model quality, and iterating on data and evaluation strategies. Your contributions will help translate cutting-edge ML ideas into reliable, production-ready systems that solve real-world problems.
This role is ideal for candidates who enjoy hands-on engineering, want to build deep intuition for ML systems, and are excited about working on LLMs and reinforcement learning in practice, not just in theory.
Responsibilities
Apply post-training techniques (e.g. RLVR, RLHF, GRPO etc.) techniques to improve model performance.
Build and maintain evaluation pipelines to measure model performance across tasks and domains.
Debug issues across the ML stack, including data pipelines, training jobs, model outputs and mixed or lower precision computation.
Collaborate with researchers to translate ML ideas into efficient, scalable implementation.
Design, implement, and scale ML pipelines across all stages of LLM development (pretraining, fine-tuning, alignment).
Work with large datasets, including dataset generation, filtering, and synthetic data approaches.
Optimize training and inference workflows for performance, efficiency, and reliability.
Contribute high-quality, maintainable code to shared ML infrastructure.
Skills & Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
4+ years of experience (including internships, research, or industry experience) working with machine learning systems; we are hiring multiple positions for various levels.
Strong programming skills in Python.
Experience with ML frameworks such as PyTorch.
Solid understanding of machine learning fundamentals.
Familiarity with deep learning architectures, particularly transformers.
Ability to read and understand modern ML papers and implement key ideas.
Preferred Skills & Qualifications
Experience working with large language models (training, fine-tuning, and evaluation).
Familiarity with reinforcement learning concepts.
Experience with distributed training frameworks (e.g., FSDP, Megatron).
Experience working with large-scale datasets and data pipelines.
Experience debugging or optimizing ML systems for performance.
• Contributions to meaningful codebases, projects, or open-source systems
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nAs an Applied Machine Learning Research Scientist at Cerebras, you will play a key role in turning modern machine learning techniques into scalable, high-performance systems. This role sits at the intersection of modeling and systems focused not on publishing new algorithms, but on understanding how they work and making them run effectively at scale. Your work will directly impact how large language models (LLMs) are trained, optimized, and deployed on one of the most advanced AI platforms in the world. \n\nYou will work closely with researchers and senior engineers to implement and improve workflows for LLM pretraining, fine-tuning, and reinforcement learning-based post-training. This includes building training pipelines, debugging complex system behaviors, improving model quality, and iterating on data and evaluation strategies. Your contributions will help translate cutting-edge ML ideas into reliable, production-ready systems that solve real-world problems. \n\nThis role is ideal for candidates who enjoy hands-on engineering, want to build deep intuition for ML systems, and are excited about working on LLMs and reinforcement learning in practice, not just in theory. \n\nResponsibilities \n\n - Apply post-training techniques (e.g. RLVR, RLHF, GRPO etc.) techniques to improve model performance.\n\n - Build and maintain evaluation pipelines to measure model performance across tasks and domains.\n\n - Debug issues across the ML stack, including data pipelines, training jobs, model outputs and mixed or lower precision computation.\n\n - Collaborate with researchers to translate ML ideas into efficient, scalable implementation.\n\n - Design, implement, and scale ML pipelines across all stages of LLM development (pretraining, fine-tuning, alignment).\n\n - Work with large datasets, including dataset generation, filtering, and synthetic data approaches.\n\n - Optimize training and inference workflows for performance, efficiency, and reliability.\n\n - Contribute high-quality, maintainable code to shared ML infrastructure. \n\nSkills & Qualifications \n\n - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.\n\n - 4+ years of experience (including internships, research, or industry experience) working with machine learning systems; we are hiring multiple positions for various levels. \n\n - Strong programming skills in Python.\n\n - Experience with ML frameworks such as PyTorch.\n\n - Solid understanding of machine learning fundamentals.\n\n - Familiarity with deep learning architectures, particularly transformers.\n\n - Ability to read and understand modern ML papers and implement key ideas.\n\nPreferred Skills & Qualifications \n\n - Experience working with large language models (training, fine-tuning, and evaluation).\n\n - Familiarity with reinforcement learning concepts.\n\n - Experience with distributed training frameworks (e.g., FSDP, Megatron).\n\n - Experience working with large-scale datasets and data pipelines.\n\n - Experience debugging or optimizing ML systems for performance.\n • Contributions to meaningful codebases, projects, or open-source systems \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d65f2d36-998d-4384-8cff-36835a403ce6","title":"ML Systems Performance Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-01-21T18:30:17.035+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/d65f2d36-998d-4384-8cff-36835a403ce6","applyUrl":"https://jobs.ashbyhq.com/cerebras/d65f2d36-998d-4384-8cff-36835a403ce6/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.
Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.
Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.
Debug and understand runtime performance on the system and cluster.
Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.
Bachelors / Masters / PhD in Electrical Engineering or Computer Science.
Strong background in computer architecture.
Exposure to and understanding of low-level deep learning / LLM math.
Strong analytical and problem-solving mindset.
3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).
Experience working on CPU/GPU simulators.
Exposure to performance profiling and debug on any system pipeline.
Comfort with C++ and Python.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nEngineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.\n\n\nRESPONSIBILITIES\n\n - Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.\n\n - Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.\n\n - Debug and understand runtime performance on the system and cluster.\n\n - Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.\n\n\nREQUIREMENTS\n\n - Bachelors / Masters / PhD in Electrical Engineering or Computer Science.\n\n - Strong background in computer architecture.\n\n - Exposure to and understanding of low-level deep learning / LLM math.\n\n - Strong analytical and problem-solving mindset.\n\n - 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).\n\n - Experience working on CPU/GPU simulators.\n\n - Exposure to performance profiling and debug on any system pipeline.\n\n - Comfort with C++ and Python.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"d82f92ec-1287-469f-a5a9-2bb77e6cef2f","title":"ASIC Architect","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-07-10T19:52:48.544+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/d82f92ec-1287-469f-a5a9-2bb77e6cef2f","applyUrl":"https://jobs.ashbyhq.com/cerebras/d82f92ec-1287-469f-a5a9-2bb77e6cef2f/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Responsibilities
Translate high level architecture spec to micro-architecture feature requirements
Bring up new features in the performance/power model
Perform comprehensive PPA trade-offs for new architectural features
Extract insights for new features and micro-architecture power efficiency
Profile workloads, identify bottlenecks and project competition performance for benchmarking
Engage with SW teams for end-end application level modeling at cluster level
Identify kernel level HW acceleration level opportunities
Qualifications
Masters/PhD in Electrical/Computer Engineering
10+ years of experience across performance analysis and modeling across GPUs, CPUs or accelerator products
Strong background in computer architecture and key high level architectural trade-offs
Comfortable standing up new performance models from scratch in Python or similar analytical environments
Exposure to micro-code (kernel) performance bottlenecks and optimization techniques
Good understanding of how high-level workloads map to underlying micro-architecture is desired
Understanding of basic ML workload profiling techniques and model network architecture is preferred
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nResponsibilities\n\n - Translate high level architecture spec to micro-architecture feature requirements\n\n - Bring up new features in the performance/power model\n\n - Perform comprehensive PPA trade-offs for new architectural features\n\n - Extract insights for new features and micro-architecture power efficiency\n\n - Profile workloads, identify bottlenecks and project competition performance for benchmarking \n\n - Engage with SW teams for end-end application level modeling at cluster level\n\n - Identify kernel level HW acceleration level opportunities\n\nQualifications\n\n - Masters/PhD in Electrical/Computer Engineering \n\n - 10+ years of experience across performance analysis and modeling across GPUs, CPUs or accelerator products\n\n - Strong background in computer architecture and key high level architectural trade-offs\n\n - Comfortable standing up new performance models from scratch in Python or similar analytical environments\n\n - Exposure to micro-code (kernel) performance bottlenecks and optimization techniques\n\n - Good understanding of how high-level workloads map to underlying micro-architecture is desired\n\n - Understanding of basic ML workload profiling techniques and model network architecture is preferred\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"dbeeb53b-1bfd-4454-8285-4ec5dbceebc3","title":"Principal AI Security Engineer","department":"Security Department","team":"Security & IT","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2026-06-23T17:39:01.800+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/dbeeb53b-1bfd-4454-8285-4ec5dbceebc3","applyUrl":"https://jobs.ashbyhq.com/cerebras/dbeeb53b-1bfd-4454-8285-4ec5dbceebc3/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Cerebras is seeking a Principal AI Security Engineer to lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems.
In this role, you will design and build security controls for systems that support training, inference, model serving, customer workloads, internal automation, and AI-assisted development. You will work across product, cloud, infrastructure, identity, runtime, data, and developer platforms to protect sensitive data, enterprise and customer environments, models, tools, agents, and control planes.
This is a principal IC role for someone who can turn ambiguous AI and platform security risks into practical architecture, reusable controls, and production-ready systems that teams can adopt by default.
Define security architecture and build controls for AI platforms, training and inference workflows, model-serving systems, customer workloads, developer workflows, and agentic
Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation, auditability, and
Design runtime controls that constrain execution, access, data exposure, model and tool interaction, and blast radius.
Build security capabilities as code using infrastructure as code, configuration as code, policy as code, GitOps, CI/CD, and automated validation.
Define secure development patterns for AI systems, agents, prompts, tools, models, policies, evaluations, releases, and rollback.
Automate security reviews, policy checks, evidence collection, control validation, and remediation
Instrument AI, agent, and platform activity with telemetry, traceability, policy decisions, audit logs, anomaly signals, and response workflows.
Lead hands-on security reviews and influence product, platform, infrastructure, and security architecture through practical design changes and reusable controls.
10+ years of experience in security engineering, platform security, infrastructure security, product security, or related technical security roles.
Strong hands-on engineering ability in Python and at least one additional production
Experience designing, building, operating, and improving security controls as
Strong cloud and infrastructure security experience, preferably with AWS, including IAM, networking, secrets management, logging, and cloud-native control planes.
Deep understanding of identity and access systems, including SSO, MFA, OAuth, service accounts, workload identity, authorization, privileged access, and least privilege.
Practical experience securing runtime environments such as containers, Kubernetes, isolated workloads, secure development environments, distributed compute platforms, or production service infrastructure.
Familiarity with AI security, LLM application security, agentic workflows, MCPs, prompt injection, autonomous coding agents, or AI platform security.
Ability to reason about cross-system risk involving identity, data, models, tools, networks, workflows, approvals, and automation.
Strong written communication skills and the ability to influence senior technical stakeholders across Security, Product, IT, Infrastructure, and Engineering.
We do not expect every candidate to have worked across all of these areas, but we value depth in several:
AI, ML, training, inference, model-serving, or large-scale compute
Coding agents, agent platforms, MCP servers, internal developer platforms, or AI-assisted development environments.
Workload identity, secrets brokers, token brokers, short-lived credentials, privileged access, or zero-standing-privilege architectures.
Policy-as-code, authorization services, runtime enforcement layers, or security control
Software delivery security, including source control, CI/CD, build systems, artifacts, provenance, signing, and release gates.
Detection, investigation, and response workflows for cloud, infrastructure, identity, AI, or agent
Success in this role means shaping how Cerebras secures the systems behind AI training, inference, model serving, customer workloads, and agentic automation. You will turn emerging AI and agent risks into reusable security architecture, safer identity and authorization models, scoped tool access, runtime containment, secure software delivery paths, automated policy validation, high-signal telemetry, and controls that engineering teams can adopt by default.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nCerebras is seeking a Principal AI Security Engineer to lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems.\n\nIn this role, you will design and build security controls for systems that support training, inference, model serving, customer workloads, internal automation, and AI-assisted development. You will work across product, cloud, infrastructure, identity, runtime, data, and developer platforms to protect sensitive data, enterprise and customer environments, models, tools, agents, and control planes.\n\nThis is a principal IC role for someone who can turn ambiguous AI and platform security risks into practical architecture, reusable controls, and production-ready systems that teams can adopt by default.\n\n\nRESPONSIBILITIES\n\n - Define security architecture and build controls for AI platforms, training and inference workflows, model-serving systems, customer workloads, developer workflows, and agentic\n\n - Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation, auditability, and\n\n - Design runtime controls that constrain execution, access, data exposure, model and tool interaction, and blast radius.\n\n - Build security capabilities as code using infrastructure as code, configuration as code, policy as code, GitOps, CI/CD, and automated validation.\n\n - Define secure development patterns for AI systems, agents, prompts, tools, models, policies, evaluations, releases, and rollback.\n\n - Automate security reviews, policy checks, evidence collection, control validation, and remediation\n\n - Instrument AI, agent, and platform activity with telemetry, traceability, policy decisions, audit logs, anomaly signals, and response workflows.\n\n - Lead hands-on security reviews and influence product, platform, infrastructure, and security architecture through practical design changes and reusable controls.\n\n\nSKILLS AND QUALIFICATIONS\n\n - 10+ years of experience in security engineering, platform security, infrastructure security, product security, or related technical security roles.\n\n - Strong hands-on engineering ability in Python and at least one additional production\n\n - Experience designing, building, operating, and improving security controls as\n\n - Strong cloud and infrastructure security experience, preferably with AWS, including IAM, networking, secrets management, logging, and cloud-native control planes.\n\n - Deep understanding of identity and access systems, including SSO, MFA, OAuth, service accounts, workload identity, authorization, privileged access, and least privilege.\n\n - Practical experience securing runtime environments such as containers, Kubernetes, isolated workloads, secure development environments, distributed compute platforms, or production service infrastructure.\n\n - Familiarity with AI security, LLM application security, agentic workflows, MCPs, prompt injection, autonomous coding agents, or AI platform security.\n\n - Ability to reason about cross-system risk involving identity, data, models, tools, networks, workflows, approvals, and automation.\n\n - Strong written communication skills and the ability to influence senior technical stakeholders across Security, Product, IT, Infrastructure, and Engineering.\n\n\nRELEVANT EXPERIENCE\n\nWe do not expect every candidate to have worked across all of these areas, but we value depth in several:\n\n - AI, ML, training, inference, model-serving, or large-scale compute\n\n - Coding agents, agent platforms, MCP servers, internal developer platforms, or AI-assisted development environments.\n\n - Workload identity, secrets brokers, token brokers, short-lived credentials, privileged access, or zero-standing-privilege architectures.\n\n - Policy-as-code, authorization services, runtime enforcement layers, or security control\n\n - Software delivery security, including source control, CI/CD, build systems, artifacts, provenance, signing, and release gates.\n\n - Detection, investigation, and response workflows for cloud, infrastructure, identity, AI, or agent\n\n\nWHAT SUCCESS LOOKS LIKE\n\nSuccess in this role means shaping how Cerebras secures the systems behind AI training, inference, model serving, customer workloads, and agentic automation. You will turn emerging AI and agent risks into reusable security architecture, safer identity and authorization models, scoped tool access, runtime containment, secure software delivery paths, automated policy validation, high-signal telemetry, and controls that engineering teams can adopt by default.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"de47a79d-5ee5-4ad4-8623-49101d6de4fb","title":"ML Research Engineer (Inference)","department":"Software","team":"Software","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-04-08T20:47:23.372+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/de47a79d-5ee5-4ad4-8623-49101d6de4fb","applyUrl":"https://jobs.ashbyhq.com/cerebras/de47a79d-5ee5-4ad4-8623-49101d6de4fb/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a Research Engineer on the Inference ML team at Cerebras Systems, you will adapt today's most advanced language and vision models to run efficiently on our flagship Cerebras architecture. You'll work alongside ML researchers and engineers to design, prototype, validate, and optimize models, gaining end-to-end exposure to cutting-edge inference research on the world's fastest AI accelerator.
You will focus on pushing the frontier of speculative decoding, large-model pruning and compression, sparse attention, and sparsity-driven techniques to deliver low-latency, high-throughput inference at scale.
Responsibilities
Implement and adapt transformer-based models (NLP and/or vision) to run on Cerebras hardware
Assist in optimizing models for inference performance (latency, throughput)
Run experiments, analyze results, and support model improvements
Help bring up and validate models on the Cerebras system
Debug and troubleshoot model or system issues with guidance from senior team members
Support profiling and performance analysis using internal tools
Collaborate with cross-functional teams (ML, software, hardware) on model integration
Minimum Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
1–3 years of experience in software engineering or machine learning in a similar capacity (internships count)
Experience with Python and at least one ML framework (e.g., PyTorch, Transformers, vLLM or SGLang)
Understanding of deep learning concepts (e.g., neural networks, transformers)
Experience with Generative AI and Machine Learning systems
Strong programming skills in Python and/or C++
Preferred Qualifications
Experience with speculative decoding, neural network pruning and compression, sparse attention, quantization, sparsity, post-training techniques, and inference-focused evaluations.
Exposure to large language models or computer vision models
Experience running experiments or tuning models
Familiarity with tools like PyTorch, Hugging Face Transformers, or similar
Basic understanding of performance concepts (e.g., latency, throughput)
Experience working in Linux environments
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role \n\nAs a Research Engineer on the Inference ML team at Cerebras Systems, you will adapt today's most advanced language and vision models to run efficiently on our flagship Cerebras architecture. You'll work alongside ML researchers and engineers to design, prototype, validate, and optimize models, gaining end-to-end exposure to cutting-edge inference research on the world's fastest AI accelerator. \n\nYou will focus on pushing the frontier of speculative decoding, large-model pruning and compression, sparse attention, and sparsity-driven techniques to deliver low-latency, high-throughput inference at scale. \n\nResponsibilities \n\n - Implement and adapt transformer-based models (NLP and/or vision) to run on Cerebras hardware\n\n - Assist in optimizing models for inference performance (latency, throughput)\n\n - Run experiments, analyze results, and support model improvements\n\n - Help bring up and validate models on the Cerebras system\n\n - Debug and troubleshoot model or system issues with guidance from senior team members\n\n - Support profiling and performance analysis using internal tools\n\n - Collaborate with cross-functional teams (ML, software, hardware) on model integration\n\nMinimum Qualifications \n\n - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field\n\n - 1–3 years of experience in software engineering or machine learning in a similar capacity (internships count)\n\n - Experience with Python and at least one ML framework (e.g., PyTorch, Transformers, vLLM or SGLang)\n\n - Understanding of deep learning concepts (e.g., neural networks, transformers)\n\n - Experience with Generative AI and Machine Learning systems\n\n - Strong programming skills in Python and/or C++\n\nPreferred Qualifications \n\n - Experience with speculative decoding, neural network pruning and compression, sparse attention, quantization, sparsity, post-training techniques, and inference-focused evaluations. \n\n - Exposure to large language models or computer vision models\n\n - Experience running experiments or tuning models\n\n - Familiarity with tools like PyTorch, Hugging Face Transformers, or similar\n\n - Basic understanding of performance concepts (e.g., latency, throughput)\n\n - Experience working in Linux environments\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"e4224669-79e2-429e-9b80-988273fb8ee7","title":"Senior Front End Design Engineer (Microarchitecture)","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"India Office","secondaryLocations":[],"publishedAt":"2026-07-10T15:37:02.438+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"Karnataka","addressCountry":"India","addressLocality":"Bengaluru"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/e4224669-79e2-429e-9b80-988273fb8ee7","applyUrl":"https://jobs.ashbyhq.com/cerebras/e4224669-79e2-429e-9b80-988273fb8ee7/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
As a senior front-end design engineer, you will be a key part of the world-class team designing and developing the next generations of the Cerebras Wafer Scale Engine (WSE). This role requires deep expertise in RTL design and integration, with a strong focus on delivering high-performance, power-efficient, and scalable solutions. You will collaborate closely with the design verification, physical design, software and system teams to bring innovative semiconductor architectures from concept to production, addressing the unique challenges of building WSE systems.
Responsibilities
Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL development, Synthesis.
Work closely with PD team members for design closure to meet PPA goals.
Work closely with Design verification and DFT teams for achieving the best functional and test coverage.
Work with software and system teams to understand opportunities to deliver optimal performance and feature set for the product.
Debug silicon-level functional, timing, and power issues during bring up.
Requirements
Master’s degree in Computer Science, Electrical Engineering, or equivalent.
Can work in a hybrid work environment.
8+ years of experience in delivering complex, high performance high quality RTL designs.
Experience with Front End Chip integration and third-party IP integration.
Demonstrated experience in networking, high-performance computing, machine learning or related fields.
Proven track record of multiple silicon success.
Experience collaborating with external vendors.
Networking stack experience including TCP/IP, RDMA and Ethernet.
Knowledge of PCIe, CPU interfaces and Serdes technology.
Working knowledge of scripting tools : Python, TCL.
Assets
Experience with FPGA development toolchain, including Place and Route, Floor planning and Timing Analysis is a plus.
Experience managing external ASIC vendor through product development cycle.
Location: Bangalore, India
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n \n\nAbout The Role\n\nAs a senior front-end design engineer, you will be a key part of the world-class team designing and developing the next generations of the Cerebras Wafer Scale Engine (WSE). This role requires deep expertise in RTL design and integration, with a strong focus on delivering high-performance, power-efficient, and scalable solutions. You will collaborate closely with the design verification, physical design, software and system teams to bring innovative semiconductor architectures from concept to production, addressing the unique challenges of building WSE systems.\n\n \n\nResponsibilities\n\n - Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL development, Synthesis.\n\n - Work closely with PD team members for design closure to meet PPA goals.\n\n - Work closely with Design verification and DFT teams for achieving the best functional and test coverage.\n\n - Work with software and system teams to understand opportunities to deliver optimal performance and feature set for the product.\n\n - Debug silicon-level functional, timing, and power issues during bring up.\n\nRequirements\n\n - Master’s degree in Computer Science, Electrical Engineering, or equivalent.\n\n - Can work in a hybrid work environment. \n\n - 8+ years of experience in delivering complex, high performance high quality RTL designs.\n\n - Experience with Front End Chip integration and third-party IP integration.\n\n - Demonstrated experience in networking, high-performance computing, machine learning or related fields.\n\n - Proven track record of multiple silicon success.\n\n - Experience collaborating with external vendors.\n\n - Networking stack experience including TCP/IP, RDMA and Ethernet.\n\n - Knowledge of PCIe, CPU interfaces and Serdes technology.\n\n - Working knowledge of scripting tools : Python, TCL.\n\nAssets\n\n - Experience with FPGA development toolchain, including Place and Route, Floor planning and Timing Analysis is a plus.\n\n - Experience managing external ASIC vendor through product development cycle.\n\n \n\nLocation: Bangalore, India\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"e825320a-b21f-40b0-9318-e71548f27640","title":"Senior Inference Platform SDET","department":"Software","team":"Cloud","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-07-13T18:51:21.315+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/e825320a-b21f-40b0-9318-e71548f27640","applyUrl":"https://jobs.ashbyhq.com/cerebras/e825320a-b21f-40b0-9318-e71548f27640/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are looking for an Inference Platform SDET to join the Inference Service Quality team at Cerebras and work on the inference platform. This team sits at the intersection of distributed systems, cloud and cluster infrastructure, and the software stack that serves the world's fastest AI inference.
In this role, you will own the quality and reliability of the infrastructure that deploys and runs the Cerebras Inference Platform — from CI/CD pipelines and Kubernetes-based deployments to ingress, load balancing, and service discovery. You will validate the platform both in cloud environments and on real Cerebras clusters, working side by side with the Inference Platform development team to catch issues before our customers do.
This is an excellent opportunity for engineers who enjoy infrastructure, automation, and debugging across the full deployment stack, and who want to ensure that a platform serving inference at massive scale stays fast, reliable, and production-ready.
Responsibilities
Design, build, and maintain test infrastructure and automation for deploying and validating the Cerebras Inference Platform.
Validate the platform across environments — from cloud-managed Kubernetes to deployments running on Cerebras hardware.
Test and verify deployment infrastructure including Kubernetes workloads, CI/CD pipelines, ingress and service discovery, NGINX, and load balancing.
Collaborate closely with the Inference Platform development team to ensure new features and platform capabilities ship reliably.
Investigate and debug complex issues spanning networking, orchestration, deployment, and distributed services.
Develop and maintain testbeds used to validate platform performance, scalability, and reliability.
Identify failure points, bottlenecks, and edge cases that impact platform stability and inference performance.
Contribute to test plans and validation strategies for new platform features and releases.
Improve observability, diagnostics, and debugging workflows across the inference platform stack.
Partner with engineering teams to ensure high-quality, production-ready releases of the Cerebras Inference Platform.
Minimum Skills & Qualifications
5+ years of experience in software engineering, QA/quality engineering, systems engineering, or infrastructure development.
Strong programming skills in Python and/or Go (experience with both is a plus).
Experience building automation tools, testing frameworks, or internal developer tooling.
Hands-on experience with CI/CD systems (e.g., Jenkins)
Experience debugging complex systems, distributed services, or networked infrastructure.
Familiarity with systems-level development, infrastructure tooling, or platform integration.
Strong problem-solving skills and the ability to investigate issues across multiple system and infrastructure layers.
Excellent communication and collaboration skills.
Experience mentoring junior engineers
Preferred Skills
Hands-on experience with Kubernetes and container orchestration in a real production or staging environment.
Experience with cloud-managed Kubernetes such as Amazon EKS.
Experience with GitOps/deployment tooling (e.g., ArgoCD).
Familiarity with ingress controllers, service discovery, NGINX, and load balancing.
Experience with build systems such as Bazel.
Experience with cluster tooling and operations (e.g., k9s).
Exposure to performance debugging, profiling, or system observability tools.
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads
Location: Toronto / Sunnyvale
Team: Inference Service Quality
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are looking for an Inference Platform SDET to join the Inference Service Quality team at Cerebras and work on the inference platform. This team sits at the intersection of distributed systems, cloud and cluster infrastructure, and the software stack that serves the world's fastest AI inference.\n\n \n\nIn this role, you will own the quality and reliability of the infrastructure that deploys and runs the Cerebras Inference Platform — from CI/CD pipelines and Kubernetes-based deployments to ingress, load balancing, and service discovery. You will validate the platform both in cloud environments and on real Cerebras clusters, working side by side with the Inference Platform development team to catch issues before our customers do.\n\n \n\nThis is an excellent opportunity for engineers who enjoy infrastructure, automation, and debugging across the full deployment stack, and who want to ensure that a platform serving inference at massive scale stays fast, reliable, and production-ready.\n\n \n\nResponsibilities\n\n - Design, build, and maintain test infrastructure and automation for deploying and validating the Cerebras Inference Platform.\n\n - Validate the platform across environments — from cloud-managed Kubernetes to deployments running on Cerebras hardware.\n\n - Test and verify deployment infrastructure including Kubernetes workloads, CI/CD pipelines, ingress and service discovery, NGINX, and load balancing.\n\n - Collaborate closely with the Inference Platform development team to ensure new features and platform capabilities ship reliably.\n\n - Investigate and debug complex issues spanning networking, orchestration, deployment, and distributed services.\n\n - Develop and maintain testbeds used to validate platform performance, scalability, and reliability.\n\n - Identify failure points, bottlenecks, and edge cases that impact platform stability and inference performance.\n\n - Contribute to test plans and validation strategies for new platform features and releases.\n\n - Improve observability, diagnostics, and debugging workflows across the inference platform stack.\n\n - Partner with engineering teams to ensure high-quality, production-ready releases of the Cerebras Inference Platform.\n \n Minimum Skills & Qualifications\n\n - 5+ years of experience in software engineering, QA/quality engineering, systems engineering, or infrastructure development.\n\n - Strong programming skills in Python and/or Go (experience with both is a plus).\n\n - Experience building automation tools, testing frameworks, or internal developer tooling.\n\n - Hands-on experience with CI/CD systems (e.g., Jenkins)\n\n - Experience debugging complex systems, distributed services, or networked infrastructure.\n\n - Familiarity with systems-level development, infrastructure tooling, or platform integration.\n\n - Strong problem-solving skills and the ability to investigate issues across multiple system and infrastructure layers.\n\n - Excellent communication and collaboration skills.\n\n - Experience mentoring junior engineers\n\nPreferred Skills\n\n - Hands-on experience with Kubernetes and container orchestration in a real production or staging environment.\n\n - Experience with cloud-managed Kubernetes such as Amazon EKS.\n\n - Experience with GitOps/deployment tooling (e.g., ArgoCD).\n\n - Familiarity with ingress controllers, service discovery, NGINX, and load balancing.\n\n - Experience with build systems such as Bazel.\n\n - Experience with cluster tooling and operations (e.g., k9s).\n\n - Exposure to performance debugging, profiling, or system observability tools.\n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads\n\nLocation: Toronto / Sunnyvale\n\nTeam: Inference Service Quality\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ea0a48cf-8c1d-444c-9a69-a5e100c311e6","title":"Senior Accountant ","department":"Commercial Operations Departments","team":"Finance","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-05-26T20:33:08.186+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/ea0a48cf-8c1d-444c-9a69-a5e100c311e6","applyUrl":"https://jobs.ashbyhq.com/cerebras/ea0a48cf-8c1d-444c-9a69-a5e100c311e6/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Senior Operations Accountant will be a key contributor to the Finance and Operations teams, reporting to the Senior Cost Accounting Manager. This role is designed for a detail-oriented professional who excels in fast-paced environments and can derive insights from complex manufacturing and inventory data. You will support the end-to-end execution of cost accounting and fixed asset processes.
Cost Capitalization & Inventory Accounting
Execute monthly inventory reconciliations and post all related journal entries.
Perform calculations for inventory rebates, wafer manufacturing yield losses, and monthly facilities allocations.
Accrue and capitalize freight and tariff costs on a monthly basis.
Ensure proper inventory classification across Raw Materials (RM), Work-in-Process (WIP), and Finished Goods (FG).
Support the coordination of physical inventory counts with Operations and external auditors.
Fixed Assets & Capital Expenditure
Manage the end-to-end fixed asset lifecycle, including additions, disposals, and monthly depreciation runs.
Track and account for internal deployments of inventory to Property, Plant, and Equipment (PPE).
Maintain the fixed asset register, ensuring accurate classification and useful life assignments in accordance with GAAP.
Monitor Construction-in-Progress (CIP) accounts and ensure timely capitalization of completed projects.
Support the audit of fixed assets, including periodic physical tagging and verification of equipment.
Manufacturing & COGS Analysis
Analyze Finished Goods movements to ensure accurate accounting for COGS and RMAs.
Review COGS transactions for completeness and perform gross margin flux analysis.
Capitalize manufacturing overhead and operational costs to ensure accurate variance analysis.
Audit & Cross-Functional Support
Prepare schedules and provide documentation for internal and external audit requests related to inventory, cost, and fixed assets.
Partner with Supply Chain and Procurement to validate inventory movements and system accuracy.
Education: Bachelor’s degree in Accounting, Finance, or a related field.
Certification: CPA or CMA preferred, with strong knowledge of GAAP, inventory costing methodologies, and fixed asset accounting.
Experience: 4+ years of progressive accounting experience, with a focus on manufacturing, hardware, or infrastructure-intensive environments.
Systems: Strong proficiency in NetSuite and advanced Excel skills (e.g., pivot tables, VLOOKUPs, data modeling).
Attributes: Ability to work with high volumes of unstructured data and a desire to optimize processes in a high-growth environment.
Location: Sunnyvale, CA (Hybrid: 3 days per week in-office)
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nThe Senior Operations Accountant will be a key contributor to the Finance and Operations teams, reporting to the Senior Cost Accounting Manager. This role is designed for a detail-oriented professional who excels in fast-paced environments and can derive insights from complex manufacturing and inventory data. You will support the end-to-end execution of cost accounting and fixed asset processes.\n\n\nRESPONSIBILITIES\n\nCost Capitalization & Inventory Accounting\n\n - Execute monthly inventory reconciliations and post all related journal entries.\n\n - Perform calculations for inventory rebates, wafer manufacturing yield losses, and monthly facilities allocations.\n\n - Accrue and capitalize freight and tariff costs on a monthly basis.\n\n - Ensure proper inventory classification across Raw Materials (RM), Work-in-Process (WIP), and Finished Goods (FG).\n\n - Support the coordination of physical inventory counts with Operations and external auditors.\n\nFixed Assets & Capital Expenditure\n\n - Manage the end-to-end fixed asset lifecycle, including additions, disposals, and monthly depreciation runs.\n\n - Track and account for internal deployments of inventory to Property, Plant, and Equipment (PPE).\n\n - Maintain the fixed asset register, ensuring accurate classification and useful life assignments in accordance with GAAP.\n\n - Monitor Construction-in-Progress (CIP) accounts and ensure timely capitalization of completed projects.\n\n - Support the audit of fixed assets, including periodic physical tagging and verification of equipment.\n\nManufacturing & COGS Analysis\n\n - Analyze Finished Goods movements to ensure accurate accounting for COGS and RMAs.\n\n - Review COGS transactions for completeness and perform gross margin flux analysis.\n\n - Capitalize manufacturing overhead and operational costs to ensure accurate variance analysis.\n\nAudit & Cross-Functional Support\n\n - Prepare schedules and provide documentation for internal and external audit requests related to inventory, cost, and fixed assets.\n\n - Partner with Supply Chain and Procurement to validate inventory movements and system accuracy.\n\n\nQUALIFICATIONS\n\n - Education: Bachelor’s degree in Accounting, Finance, or a related field.\n\n - Certification: CPA or CMA preferred, with strong knowledge of GAAP, inventory costing methodologies, and fixed asset accounting.\n\n - Experience: 4+ years of progressive accounting experience, with a focus on manufacturing, hardware, or infrastructure-intensive environments.\n\n - Systems: Strong proficiency in NetSuite and advanced Excel skills (e.g., pivot tables, VLOOKUPs, data modeling).\n\n - Attributes: Ability to work with high volumes of unstructured data and a desire to optimize processes in a high-growth environment.\n\n\nADDITIONAL INFORMATION\n\n - Location: Sunnyvale, CA (Hybrid: 3 days per week in-office)\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ea44d96f-37e9-4d59-8749-621013176832","title":"Senior Runtime Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"US and Canada Offices","secondaryLocations":[],"publishedAt":"2025-10-28T13:38:32.141+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/cerebras/ea44d96f-37e9-4d59-8749-621013176832","applyUrl":"https://jobs.ashbyhq.com/cerebras/ea44d96f-37e9-4d59-8749-621013176832/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are building the next generation of large-scale AI systems that power training and inference workloads at unprecedented scale and efficiency.
You will design and develop high-performance distributed software that orchestrates massive compute and data pipelines across heterogeneous clusters. Your work will push the limits of concurrency, throughput, and scalability—enabling efficient execution of models at massive scale. This role sits at the intersection of systems engineering and machine learning performance, demanding both architectural depth and low-level implementation skills. You will help shape how models are executed and optimized end-to-end, from data ingestion to distributed execution, across cutting-edge hardware platforms.
We’re hiring for runtime roles across both Training and Inference.
Responsibilities
Design and implement distributed runtime components to efficiently manage large-scale execution workloads.
Develop and optimize high-performance data and communication pipelines that fully utilize CPU, memory, storage, and network resources.
Enable scalable execution across multiple compute nodes, ensuring high concurrency and minimal bottlenecks.
Collaborate closely with ML and compiler teams to integrate new model architectures, training regimes, and hardware-specific optimizations.
Diagnose and resolve complex performance issues across the software stack using profiling and instrumentation tools.
Contribute to overall system design, architecture reviews, and roadmap planning for large-scale AI workloads.
Skills & Qualifications
3+ years of experience developing high-performance or distributed system software.
Strong programming skills in C/C++, with expertise in multi-threading, memory management, and performance optimization.
Experience with distributed systems, networking, or inter-process communication.
Solid understanding of data structures, concurrency, and system-level resource management (CPU, I/O, and memory).
Proven ability to debug, profile, and optimize code across scales—from threads to clusters.
Bachelor’s, Master’s, or equivalent experience in Computer Science, Electrical Engineering, or related field.
Preferred Skills & Qualifications
Familiarity with machine learning training or inference pipelines, especially distributed training and large-model scaling.
Exposure to Python and PyTorch, particularly in the context of model training or performance tuning.
Experience with compiler internals, custom hardware interfaces, or low-level protocol design.
Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.
Deep curiosity about how to unlock new levels of performance for large-scale AI workloads.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n \n\nAbout The Role\n\nWe are building the next generation of large-scale AI systems that power training and inference workloads at unprecedented scale and efficiency.\n\nYou will design and develop high-performance distributed software that orchestrates massive compute and data pipelines across heterogeneous clusters. Your work will push the limits of concurrency, throughput, and scalability—enabling efficient execution of models at massive scale. This role sits at the intersection of systems engineering and machine learning performance, demanding both architectural depth and low-level implementation skills. You will help shape how models are executed and optimized end-to-end, from data ingestion to distributed execution, across cutting-edge hardware platforms.\n\nWe’re hiring for runtime roles across both Training and Inference.\n\nResponsibilities\n\n - Design and implement distributed runtime components to efficiently manage large-scale execution workloads.\n\n - Develop and optimize high-performance data and communication pipelines that fully utilize CPU, memory, storage, and network resources.\n\n - Enable scalable execution across multiple compute nodes, ensuring high concurrency and minimal bottlenecks.\n\n - Collaborate closely with ML and compiler teams to integrate new model architectures, training regimes, and hardware-specific optimizations.\n\n - Diagnose and resolve complex performance issues across the software stack using profiling and instrumentation tools.\n\n - Contribute to overall system design, architecture reviews, and roadmap planning for large-scale AI workloads.\n\nSkills & Qualifications\n\n - 3+ years of experience developing high-performance or distributed system software.\n\n - Strong programming skills in C/C++, with expertise in multi-threading, memory management, and performance optimization.\n\n - Experience with distributed systems, networking, or inter-process communication.\n\n - Solid understanding of data structures, concurrency, and system-level resource management (CPU, I/O, and memory).\n\n - Proven ability to debug, profile, and optimize code across scales—from threads to clusters.\n\n - Bachelor’s, Master’s, or equivalent experience in Computer Science, Electrical Engineering, or related field.\n\nPreferred Skills & Qualifications\n\n - Familiarity with machine learning training or inference pipelines, especially distributed training and large-model scaling.\n\n - Exposure to Python and PyTorch, particularly in the context of model training or performance tuning.\n\n - Experience with compiler internals, custom hardware interfaces, or low-level protocol design.\n\n - Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.\n\n - Deep curiosity about how to unlock new levels of performance for large-scale AI workloads.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"ef15b7be-2fa3-4343-81aa-47ef65171af0","title":"Staff Software Engineer, Inference Platform ","department":"Software","team":"Cloud","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[{"location":"Toronto Office","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}}}],"publishedAt":"2026-06-19T21:24:23.681+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/ef15b7be-2fa3-4343-81aa-47ef65171af0","applyUrl":"https://jobs.ashbyhq.com/cerebras/ef15b7be-2fa3-4343-81aa-47ef65171af0/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We're hiring a Staff Engineer to help lead, drive, and contribute to projects on our Inference Platform team. Our team primarily owns the orchestration layer that runs inference on our datacenter clusters, connecting cloud components with machine learning services. We are often the first team to face problems that haven't been solved yet, leading solutions across Kubernetes operators, service security policies, and CI/CD.
If you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.
Responsibilities
Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.
Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.
Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.
Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.
Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.
Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.
Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.
Skills & Qualifications
8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.
Deep expertise in distributed systems architecture, ideally with Kubernetes.
Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.
Experience with security (certificates, TLS, mTLS).
Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.
Strong proficiency in backend or systems languages such as Go or C++, with the expectation that you can contribute production code directly.
Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.
Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.
Preferred Skills & Qualifications
Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.
Location: Sunnyvale or Toronto preferred
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe're hiring a Staff Engineer to help lead, drive, and contribute to projects on our Inference Platform team. Our team primarily owns the orchestration layer that runs inference on our datacenter clusters, connecting cloud components with machine learning services. We are often the first team to face problems that haven't been solved yet, leading solutions across Kubernetes operators, service security policies, and CI/CD.\n\nIf you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.\n\nResponsibilities\n\n - Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.\n\n - Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.\n\n - Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.\n\n - Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.\n\n - Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.\n\n - Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.\n\n - Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.\n\nSkills & Qualifications\n\n - 8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.\n\n - Deep expertise in distributed systems architecture, ideally with Kubernetes.\n\n - Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.\n\n - Experience with security (certificates, TLS, mTLS).\n\n - Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.\n\n - Strong proficiency in backend or systems languages such as Go or C++, with the expectation that you can contribute production code directly.\n\n - Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.\n\n - Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.\n\n - Preferred Skills & Qualifications\n\n - Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.\n\nLocation: Sunnyvale or Toronto preferred\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"efc5bdc8-62df-4fc3-881c-a96ca1705de7","title":"Network Engineer ","department":"Software","team":"Software","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-06-03T18:37:00.621+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/efc5bdc8-62df-4fc3-881c-a96ca1705de7","applyUrl":"https://jobs.ashbyhq.com/cerebras/efc5bdc8-62df-4fc3-881c-a96ca1705de7/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
We are looking for a Network Architect to join our Cluster Engineering Team and help shape the front-end datacenter and interconnect fabric for the current and next generations of our AI clusters. You will partner closely with hardware vendors, internal networking teams, and industry peers to define best-in-class network architectures that deliver resilient, reliable, and high-throughput connectivity for large-scale AI workloads.
This is a deeply technical role that spans the full stack, from host-side networking and NIC behavior up through cluster-level coordination and requires fluency across diverse hardware components (including network switches, NICs, and the Accelerator Compute Engine) and the software layers that drive them. You will own proof-of-concept work for new network designs and features, and you will be the central technical voice for network reliability across the organization.
Design and architect front-end network fabrics for AI/ML and HPC clusters, optimizing for high resource utilization, low latency, and high-throughput communication.
Build proof-of-concept implementations of new network designs and features, and drive them from prototype through production rollout.
Identify and resolve performance and efficiency bottlenecks across the host-NIC-fabric
Automate the deployment, configuration, and validation of network infrastructure using Python, including topology provisioning, fabric bring-up, config generation, and regression Strong programming skills are essential; this role builds tools, not just runbooks.
Stand up and operate SRE-grade telemetry and observability for the cluster network: streaming telemetry (gNMI, OpenConfig, sFlow/IPFIX), metrics pipelines, alerting, and incident workflows. Define the SLIs/SLOs that govern network reliability and drive blameless post-incident analysis.
Lead network debugging in large distributed-systems environments spanning multiple platforms and protocols, including deep dives into RoCEv2, PFC/DCQCN, ECMP hashing, congestion behavior, and packet-level forensics.
Lead cross-functional, multi-phase technical projects spanning hardware, firmware, host networking, and cluster software.
Collaborate with vendors and industry partners to shape network hardware and feature roadmaps.
Represent the company in industry forums, standards bodies, and technical communities.
Serve as the central point of contact for network reliability issues across the cluster.
Ph.D. in Computer Science or Electrical Engineering with 5+ years of industry experience, or Master's in CS/EE with 10+ years of industry experience.
Solid experience in designing large-scale networks in datacenter and cloud environments.
Extensive hands-on experience debugging networking issues in large distributed systems with multiple platforms and protocols.
Demonstrated track record leading multi-phase, multi-team technical projects to completion.
Deep expertise across networking platforms: Juniper, Arista, Cisco, and open-box / disaggregated NOS architectures (SONiC).
Strong working knowledge of networking protocols and fabric technologies: VXLAN, EVPN, RoCEv2, BGP, DCQCN, PFC, ECN, and streaming telemetry.
Programming and automation: proficiency in Python (and/or Go) for building network automation, validation, and tooling. Comfort with config generation frameworks (Ansible, Jinja2), gNMI, and CI/CD pipelines for network infrastructure.
SRE and observability: hands-on experience with streaming telemetry pipelines, time-series databases (Prometheus, InfluxDB), visualization (Grafana), log aggregation, and modern incident-management Ability to define SLIs/SLOs and instrument the network for proactive reliability.
Familiarity with network visibility, management, and packet-capture/analysis tools.
Prior experience at hyperscalers or cloud service providers.
Experience with AI/ML or HPC cluster networking, including lossless Ethernet design, rail-optimized topologies, and collective-communication traffic patterns.
Track record of contributions to open-source networking projects, standards bodies, or industry conferences.
You'll work on networks that move data at a scale and density few teams ever touch, with direct impact on training and inference performance for some of the largest AI systems in the world. You'll have the autonomy to shape architecture decisions, the resources to prototype real hardware, and a peer group that takes both engineering rigor and operational reliability seriously.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nWe are looking for a Network Architect to join our Cluster Engineering Team and help shape the front-end datacenter and interconnect fabric for the current and next generations of our AI clusters. You will partner closely with hardware vendors, internal networking teams, and industry peers to define best-in-class network architectures that deliver resilient, reliable, and high-throughput connectivity for large-scale AI workloads.\n\nThis is a deeply technical role that spans the full stack, from host-side networking and NIC behavior up through cluster-level coordination and requires fluency across diverse hardware components (including network switches, NICs, and the Accelerator Compute Engine) and the software layers that drive them. You will own proof-of-concept work for new network designs and features, and you will be the central technical voice for network reliability across the organization.\n\n\nWHAT YOU'LL DO\n\n - Design and architect front-end network fabrics for AI/ML and HPC clusters, optimizing for high resource utilization, low latency, and high-throughput communication.\n\n - Build proof-of-concept implementations of new network designs and features, and drive them from prototype through production rollout.\n\n - Identify and resolve performance and efficiency bottlenecks across the host-NIC-fabric\n\n - Automate the deployment, configuration, and validation of network infrastructure using Python, including topology provisioning, fabric bring-up, config generation, and regression Strong programming skills are essential; this role builds tools, not just runbooks.\n\n - Stand up and operate SRE-grade telemetry and observability for the cluster network: streaming telemetry (gNMI, OpenConfig, sFlow/IPFIX), metrics pipelines, alerting, and incident workflows. Define the SLIs/SLOs that govern network reliability and drive blameless post-incident analysis.\n\n - Lead network debugging in large distributed-systems environments spanning multiple platforms and protocols, including deep dives into RoCEv2, PFC/DCQCN, ECMP hashing, congestion behavior, and packet-level forensics.\n\n - Lead cross-functional, multi-phase technical projects spanning hardware, firmware, host networking, and cluster software.\n\n - Collaborate with vendors and industry partners to shape network hardware and feature roadmaps. \n\n - Represent the company in industry forums, standards bodies, and technical communities. \n\n - Serve as the central point of contact for network reliability issues across the cluster. \n\n\nSKILLS & QUALIFICATIONS\n\n - Ph.D. in Computer Science or Electrical Engineering with 5+ years of industry experience, or Master's in CS/EE with 10+ years of industry experience.\n\n - Solid experience in designing large-scale networks in datacenter and cloud environments. \n\n - Extensive hands-on experience debugging networking issues in large distributed systems with multiple platforms and protocols.\n\n - Demonstrated track record leading multi-phase, multi-team technical projects to completion. \n\n\nTECHNICAL SKILLS\n\n - Deep expertise across networking platforms: Juniper, Arista, Cisco, and open-box / disaggregated NOS architectures (SONiC).\n\n - Strong working knowledge of networking protocols and fabric technologies: VXLAN, EVPN, RoCEv2, BGP, DCQCN, PFC, ECN, and streaming telemetry.\n\n - Programming and automation: proficiency in Python (and/or Go) for building network automation, validation, and tooling. Comfort with config generation frameworks (Ansible, Jinja2), gNMI, and CI/CD pipelines for network infrastructure.\n\n - SRE and observability: hands-on experience with streaming telemetry pipelines, time-series databases (Prometheus, InfluxDB), visualization (Grafana), log aggregation, and modern incident-management Ability to define SLIs/SLOs and instrument the network for proactive reliability.\n\n - Familiarity with network visibility, management, and packet-capture/analysis tools. \n\n\nSTRONGLY PREFERRED\n\n - Prior experience at hyperscalers or cloud service providers. \n\n - Experience with AI/ML or HPC cluster networking, including lossless Ethernet design, rail-optimized topologies, and collective-communication traffic patterns.\n\n - Track record of contributions to open-source networking projects, standards bodies, or industry conferences.\n\n\nWHY JOIN US\n\nYou'll work on networks that move data at a scale and density few teams ever touch, with direct impact on training and inference performance for some of the largest AI systems in the world. You'll have the autonomy to shape architecture decisions, the resources to prototype real hardware, and a peer group that takes both engineering rigor and operational reliability seriously.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"f4d29622-03e6-41e6-acec-8a22e89c51ee","title":"Design Validation Test - Lead/Principal Engineer","department":"Hardware Departments","team":"Systems","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-03-04T08:23:18.909+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/f4d29622-03e6-41e6-acec-8a22e89c51ee","applyUrl":"https://jobs.ashbyhq.com/cerebras/f4d29622-03e6-41e6-acec-8a22e89c51ee/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We are seeking a hands‑on DVT Technical Lead (Individual Contributor) to own and drive the Design Validation Test (DVT) process end‑to‑end across complex electrical engineering boards and full systems. You will define validation strategy, build test plans and infrastructure, lead deep debug and root‑cause analysis (RCA), and drive closure through design changes and re‑test. The domain includes difficult power delivery technology, fast high‑speed I/O, and electro‑mechanical systems with thermal, optics, and high‑power constraints. People management is not required (mentoring is a plus).
What You’ll Own
1) Board / Subassembly DVT (EE-heavy)
Own DVT for complex PCBAs and subassemblies from first power‑on through design sign‑off.
Power validation: power‑up/down sequencing, regulator/hotswap behavior, rail margining, DC IR drop, and AC noise/ripple characterization.
Clock distribution validation and high‑speed I/O interface validation (e.g., Ethernet/PCIe-class links, board‑to‑board connectors and cabling).
Low‑speed system management interface validation (e.g., I2C/SPI/USB) and debug of intermittent or systemic failures.
Stress/environmental testing (extended runtime, temperature cycling) and characterization under margined conditions.
2) System-level DVT (integration + electro-mechanical)
Own system integration validation planning and execution across representative configurations and operating envelopes.
Drive readiness and execution across lab and chamber environments, including dependency management (test scripts, instrumentation, SW readiness, sample availability).
Validate and debug system-level issues spanning electrical, mechanical, thermal, and optics interactions.
Partner with reliability and manufacturing teams to ensure DVT coverage supports ramp readiness and reduces escapes.
Key Responsibilities
DVT Strategy, Plans, and Coverage
Define a risk‑based DVT strategy spanning board/subassembly engineering validation through system integration validation.
Author and maintain DVT plans, procedures, and reports with crisp pass/fail criteria and coverage rationale.
Establish stage gates and readiness reviews for execution quality (fixtures, instrumentation, scripts, SW readiness).
Hands-on Validation, Debug, and Closure
Build and own benchtop and rack-level validation setups that are repeatable and automation‑friendly.
Lead RCA for validation failures; drive corrective actions with design teams; verify fixes through re‑test and data review.
Execute and interpret power integrity/stability measurements (voltage/current stability, droop, ripple/noise, IR drop) and close gaps to requirements.
Validate high‑speed interconnect performance and margin; isolate failures across channel, connector/cable, PHY, and firmware/diagnostics layers.
DVT Infrastructure, Automation, and Data
Partner with diagnostics/software to improve DVT throughput via scripting, logging, and standardized test stages.
Define required data capture and reporting standards to accelerate debug and support release gating.
Drive continual improvements to test coverage, efficiency, and repeatability across builds.
Cross-functional Technical Leadership
Align EE/ME/FW/Diagnostics/Reliability/Manufacturing on priorities, schedules, and closure criteria.
Influence design-for-testability improvements (debug visibility, margining hooks, instrumentation points, serviceability).
Minimum Qualifications
BS/MS in Electrical or Computer Engineering (or equivalent experience).
8–15+ years of hardware validation/DVT experience on complex board and system-level products.
Demonstrated ownership of board bring‑up and DVT execution: test plan creation, instrumentation, debug, and closure.
Strong background in power delivery validation and measurement (sequencing, margining, droop, ripple/noise, IR drop).
Strong background in high‑speed I/O validation and debug (PCIe/Ethernet‑class links; channel and system-level troubleshooting).
Proficiency with lab equipment: oscilloscopes, logic analyzers, power supplies/analyzers, DC electronic loads; VNAs/BERTs as applicable.
Strong written and verbal communication; ability to present results and drive decisions with data.
Preferred / Nice-to-Have
Experience with rack-scale and/or liquid-cooled systems; validation in environmental chambers.
Experience supporting compliance/safety/EMC efforts as part of DVT readiness.
Python (or similar) for test automation and data analysis; experience integrating results into dashboards/CI workflows.
Experience mentoring engineers/technicians as an informal technical leader.
Success Measures
DVT plans are complete, prioritized, and executable; coverage gaps are explicit and tracked to closure.
Validation failures convert quickly into RCAs and verified fixes; DVT becomes repeatable and less “heroic.”
Power delivery and high-speed I/O risks are discovered early and do not surprise late in system integration.
Test automation/data capture improves cycle time and increases confidence in release gating.
Location :Sunnyvale, California
The base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout the Role\n\nWe are seeking a hands‑on DVT Technical Lead (Individual Contributor) to own and drive the Design Validation Test (DVT) process end‑to‑end across complex electrical engineering boards and full systems. You will define validation strategy, build test plans and infrastructure, lead deep debug and root‑cause analysis (RCA), and drive closure through design changes and re‑test. The domain includes difficult power delivery technology, fast high‑speed I/O, and electro‑mechanical systems with thermal, optics, and high‑power constraints. People management is not required (mentoring is a plus).\n\n \n\nWhat You’ll Own\n\n1) Board / Subassembly DVT (EE-heavy)\n\n - Own DVT for complex PCBAs and subassemblies from first power‑on through design sign‑off.\n\n - Power validation: power‑up/down sequencing, regulator/hotswap behavior, rail margining, DC IR drop, and AC noise/ripple characterization.\n\n - Clock distribution validation and high‑speed I/O interface validation (e.g., Ethernet/PCIe-class links, board‑to‑board connectors and cabling).\n\n - Low‑speed system management interface validation (e.g., I2C/SPI/USB) and debug of intermittent or systemic failures.\n\n - Stress/environmental testing (extended runtime, temperature cycling) and characterization under margined conditions.\n\n \n\n2) System-level DVT (integration + electro-mechanical)\n\n - Own system integration validation planning and execution across representative configurations and operating envelopes.\n\n - Drive readiness and execution across lab and chamber environments, including dependency management (test scripts, instrumentation, SW readiness, sample availability).\n\n - Validate and debug system-level issues spanning electrical, mechanical, thermal, and optics interactions.\n\n - Partner with reliability and manufacturing teams to ensure DVT coverage supports ramp readiness and reduces escapes.\n\n \n\nKey Responsibilities\n\nDVT Strategy, Plans, and Coverage\n\n - Define a risk‑based DVT strategy spanning board/subassembly engineering validation through system integration validation.\n\n - Author and maintain DVT plans, procedures, and reports with crisp pass/fail criteria and coverage rationale.\n\n - Establish stage gates and readiness reviews for execution quality (fixtures, instrumentation, scripts, SW readiness).\n\n \n\nHands-on Validation, Debug, and Closure\n\n - Build and own benchtop and rack-level validation setups that are repeatable and automation‑friendly.\n\n - Lead RCA for validation failures; drive corrective actions with design teams; verify fixes through re‑test and data review.\n\n - Execute and interpret power integrity/stability measurements (voltage/current stability, droop, ripple/noise, IR drop) and close gaps to requirements.\n\n - Validate high‑speed interconnect performance and margin; isolate failures across channel, connector/cable, PHY, and firmware/diagnostics layers.\n\n \n\nDVT Infrastructure, Automation, and Data\n\n - Partner with diagnostics/software to improve DVT throughput via scripting, logging, and standardized test stages.\n\n - Define required data capture and reporting standards to accelerate debug and support release gating.\n\n - Drive continual improvements to test coverage, efficiency, and repeatability across builds.\n\n \n\nCross-functional Technical Leadership\n\n - Align EE/ME/FW/Diagnostics/Reliability/Manufacturing on priorities, schedules, and closure criteria.\n\n - Influence design-for-testability improvements (debug visibility, margining hooks, instrumentation points, serviceability).\n\n \n\nMinimum Qualifications\n\n - BS/MS in Electrical or Computer Engineering (or equivalent experience).\n\n - 8–15+ years of hardware validation/DVT experience on complex board and system-level products.\n\n - Demonstrated ownership of board bring‑up and DVT execution: test plan creation, instrumentation, debug, and closure.\n\n - Strong background in power delivery validation and measurement (sequencing, margining, droop, ripple/noise, IR drop).\n\n - Strong background in high‑speed I/O validation and debug (PCIe/Ethernet‑class links; channel and system-level troubleshooting).\n\n - Proficiency with lab equipment: oscilloscopes, logic analyzers, power supplies/analyzers, DC electronic loads; VNAs/BERTs as applicable.\n\n - Strong written and verbal communication; ability to present results and drive decisions with data.\n\n \n\nPreferred / Nice-to-Have\n\n - Experience with rack-scale and/or liquid-cooled systems; validation in environmental chambers.\n\n - Experience supporting compliance/safety/EMC efforts as part of DVT readiness.\n\n - Python (or similar) for test automation and data analysis; experience integrating results into dashboards/CI workflows.\n\n - Experience mentoring engineers/technicians as an informal technical leader.\n\n \n\nSuccess Measures\n\n - DVT plans are complete, prioritized, and executable; coverage gaps are explicit and tracked to closure.\n\n - Validation failures convert quickly into RCAs and verified fixes; DVT becomes repeatable and less “heroic.”\n\n - Power delivery and high-speed I/O risks are discovered early and do not surprise late in system integration.\n\n - Test automation/data capture improves cycle time and increases confidence in release gating.\n\n \n\nLocation :Sunnyvale, California\n\n \n\nThe base salary range for this position is $175,000 to $275,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"f5b09237-550f-4267-93f5-68f7ea5e59f7","title":"ML Performance Benchmarking Engineer","department":"Software","team":"Software","employmentType":"FullTime","location":"Toronto Office","secondaryLocations":[],"publishedAt":"2026-03-18T14:00:25.630+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"M5H1Z5","addressRegion":"Ontario","streetAddress":"67 Richmond St W","addressCountry":"Canada","addressLocality":"Toronto"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/f5b09237-550f-4267-93f5-68f7ea5e59f7","applyUrl":"https://jobs.ashbyhq.com/cerebras/f5b09237-550f-4267-93f5-68f7ea5e59f7/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
The Inference Core Platform group is at the heart of Cerebras' mission to deliver the world’s fastest AI inference. Our team builds the foundational software and hardware infrastructure that powers low-latency, high-speed, high-throughput deployment on the Cerebras Wafer-Scale Engine (WSE). We are responsible for the full stack—from model compilation and scheduling down to custom hardware kernels and driver development.
The ML Performance Benchmarking team plays a pivotal role in shaping the performance and scalability of AI inference on one of the most advanced computing systems ever built. We drive the bring-up of core inference capabilities and deliver performance improvements at every stage of development – from early prototyping to production deployment.
We're looking for passionate engineers to join us in redefining the limits of AI inference. If you thrive on building systems that measure, analyze, and optimize performance at scale, this is your opportunity to make a transformative impact on the future of AI.
Scope of the team includes:
Core Inference Observability – Design and implement end-to-end telemetry systems across the software stack, providing deep visibility into inference performance and enabling rapid iteration before and after deployment.
Benchmarking Infrastructure – Architect, build, and scale the automation that generates, analyzes, and visualizes performance data used to inform business decisions across engineering and leadership.
Performance Analysis – Dive deep into system behavior, dissect performance bottlenecks, and deliver actionable insights that directly influence which features ship and how they evolve.
Feature Integration – Partner closely with Core Platform teams to define rigorous testing methodologies that validate inference features for peak performance.
Skills & Qualifications
Bachelor’s or Master’s degree in Computer Engineering, Systems Engineering, or a related field.
Proficiency in Python and/or C++ programming.
Proven experience in building and scaling automated infrastructure.
Strong background in throughput and performance optimization techniques, especially in complex, large-scale systems.
Excellent problem-solving skills and a strong analytical mindset.
Demonstrated ability to dive deep into new domains.
Ability to work in a fast-paced, ambiguous, and collaborative environment.
Preferred Skills & Qualifications
Familiarity with problem-solving at the intersection of hardware and software.
Hands-on experience with AI workloads and architectures is a plus.
Location
On-site or hybrid at our Toronto office
#LI-WA1
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nAbout The Role\n\nThe Inference Core Platform group is at the heart of Cerebras' mission to deliver the world’s fastest AI inference. Our team builds the foundational software and hardware infrastructure that powers low-latency, high-speed, high-throughput deployment on the Cerebras Wafer-Scale Engine (WSE). We are responsible for the full stack—from model compilation and scheduling down to custom hardware kernels and driver development.\n\nThe ML Performance Benchmarking team plays a pivotal role in shaping the performance and scalability of AI inference on one of the most advanced computing systems ever built. We drive the bring-up of core inference capabilities and deliver performance improvements at every stage of development – from early prototyping to production deployment.\n\nWe're looking for passionate engineers to join us in redefining the limits of AI inference. If you thrive on building systems that measure, analyze, and optimize performance at scale, this is your opportunity to make a transformative impact on the future of AI.\n\nScope of the team includes:\n\n - Core Inference Observability – Design and implement end-to-end telemetry systems across the software stack, providing deep visibility into inference performance and enabling rapid iteration before and after deployment.\n\n - Benchmarking Infrastructure – Architect, build, and scale the automation that generates, analyzes, and visualizes performance data used to inform business decisions across engineering and leadership.\n\n - Performance Analysis – Dive deep into system behavior, dissect performance bottlenecks, and deliver actionable insights that directly influence which features ship and how they evolve.\n\n - Feature Integration – Partner closely with Core Platform teams to define rigorous testing methodologies that validate inference features for peak performance.\n\nSkills & Qualifications\n\n - Bachelor’s or Master’s degree in Computer Engineering, Systems Engineering, or a related field.\n\n - Proficiency in Python and/or C++ programming.\n\n - Proven experience in building and scaling automated infrastructure.\n\n - Strong background in throughput and performance optimization techniques, especially in complex, large-scale systems.\n\n - Excellent problem-solving skills and a strong analytical mindset.\n\n - Demonstrated ability to dive deep into new domains.\n\n - Ability to work in a fast-paced, ambiguous, and collaborative environment.\n\nPreferred Skills & Qualifications\n\n - Familiarity with problem-solving at the intersection of hardware and software.\n\n - Hands-on experience with AI workloads and architectures is a plus.\n\nLocation\n\n - On-site or hybrid at our Toronto office\n\n \n\n#LI-WA1\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"f6b2efb8-71b1-44b9-bbaf-42943071c7fc","title":"Manufacturing Test Development Engineer","department":"Manufacturing Departments","team":"Manufacturing","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-01-08T15:42:05.801+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/f6b2efb8-71b1-44b9-bbaf-42943071c7fc","applyUrl":"https://jobs.ashbyhq.com/cerebras/f6b2efb8-71b1-44b9-bbaf-42943071c7fc/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As a Test Development Engineer on our manufacturing team you will be working with diagnostics, system design, manufacturing, and quality teams to develop test automation solutions for our products from PCBA to system level. You will also work closely with our contract manufacturing sites to fulfill a complete test automation solution for manufacturing test data, yield improvement, and traceability.
Develop and design manufacturing test automation software/scripts to test Cerebras products from PCBA to system level.
Develop and implement GUI solutions for test automation.
Work with our contract manufacturers to develop and implement a test data reporting portal for manufacturing traceability and analysis.
Sustain our current test software and infrastructure and help root cause and resolve any manufacturing test software issues or hardware defects.
Design a web interface for user to modify/edit settings from mySQL database on AWS.
Setup the various infrastructures at our manufacturing sites to support test equipment and server operation.
Interact with contract manufacturing site for all the technical issues relating to manufacturing test.
Work with diagnostics, system design, manufacturing and quality team to bring up test automation suites for the new products.
Bachelors in computer science, electrical engineering, or other related field.
5+ years of experience in test automation, test development or related experience.
Skilled in C/C++, Visual Studio, Python programming languages.
Good knowledge of js, MySQL, SQL, SQL Server Reporting Service.
Good knowledge of Pexpect, SSH, Telnet, RS-232, bash script.
Good knowledge of Windows, Linux, Ubuntu, Centos, VNC viewer, Console server.
Debugging skills and knowledge of debugging complex software stack.
Experience in GUI development.
Experience in Web development.
Experience in API development.
The base salary range for this position is $170,000 to $210,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\n\nABOUT THE ROLE\n\nAs a Test Development Engineer on our manufacturing team you will be working with diagnostics, system design, manufacturing, and quality teams to develop test automation solutions for our products from PCBA to system level. You will also work closely with our contract manufacturing sites to fulfill a complete test automation solution for manufacturing test data, yield improvement, and traceability.\n\n\nRESPONSIBILITIES\n\n - Develop and design manufacturing test automation software/scripts to test Cerebras products from PCBA to system level.\n\n - Develop and implement GUI solutions for test automation.\n\n - Work with our contract manufacturers to develop and implement a test data reporting portal for manufacturing traceability and analysis.\n\n - Sustain our current test software and infrastructure and help root cause and resolve any manufacturing test software issues or hardware defects.\n\n - Design a web interface for user to modify/edit settings from mySQL database on AWS.\n\n - Setup the various infrastructures at our manufacturing sites to support test equipment and server operation.\n\n - Interact with contract manufacturing site for all the technical issues relating to manufacturing test.\n\n - Work with diagnostics, system design, manufacturing and quality team to bring up test automation suites for the new products.\n\n\nREQUIREMENTS\n\n - Bachelors in computer science, electrical engineering, or other related field.\n\n - 5+ years of experience in test automation, test development or related experience.\n\n - Skilled in C/C++, Visual Studio, Python programming languages.\n\n - Good knowledge of js, MySQL, SQL, SQL Server Reporting Service.\n\n - Good knowledge of Pexpect, SSH, Telnet, RS-232, bash script.\n\n - Good knowledge of Windows, Linux, Ubuntu, Centos, VNC viewer, Console server.\n\n - Debugging skills and knowledge of debugging complex software stack.\n\n\nPREFERRED SKILLS\n\n - Experience in GUI development.\n\n - Experience in Web development.\n\n - Experience in API development.\n\nThe base salary range for this position is $170,000 to $210,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."},{"id":"fd32728a-5801-42fd-aeb5-c5e4dfbd9403","title":"Sr. Staff/Staff Design Verification Engineer","department":"Hardware Departments","team":"Silicon","employmentType":"FullTime","location":"Headquarters/Sunnyvale Office","secondaryLocations":[],"publishedAt":"2026-06-04T16:45:23.692+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"postalCode":"94085","addressRegion":"California","streetAddress":"1237 E Arques Ave","addressCountry":"United States","addressLocality":"Sunnyvale"}},"jobUrl":"https://jobs.ashbyhq.com/cerebras/fd32728a-5801-42fd-aeb5-c5e4dfbd9403","applyUrl":"https://jobs.ashbyhq.com/cerebras/fd32728a-5801-42fd-aeb5-c5e4dfbd9403/application","descriptionHtml":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Key Responsibilities
Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works first silicon.
Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.
Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.
Implement tests, manage regressions, gather coverage, and debug test failures.
Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.
Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.
Continuously enhances verification infrastructure and flows to improve efficiency and quality.
Contribute to the evolution of the overall verification methodology and best practices across the organization.
Skills and Qualifications
Great debugging and problem-solving skills.
Deep knowledge of SystemVerilog testbench, DPI and UVM.
Excellent programming skills and knowledge of software engineering practices including object-oriented design.
Experience developing scalable and portable testbenches and components.
Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.
Proficient in scripting languages such as Python or Perl.
Good interpersonal skills and the ability to work as a standout colleague are a must.
Extremely self-motivated and eager to solve problems
10+ years of Design Verification experience.
Desired Skills and Qualifications
Knowledge of pipelined processor architecture.
BS or MS in Computer Science or Electrical Engineering.
10+ years of hands-on Design Verification experience.
Location: Sunnyvale, CA
The base salary range for this position is $250,000 to $300,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
","descriptionPlain":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.\n\nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\n\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\n\nKey Responsibilities\n\n - Work with architects, designers, post silicon and software engineers to ensure a high-quality design that works first silicon.\n\n - Develop and implement verification strategies, detailed tests and coverage plans based on micro-architecture.\n\n - Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage.\n\n - Implement tests, manage regressions, gather coverage, and debug test failures.\n\n - Collaborate with cross-functional teams including architecture, RTL design, physical design, firmware, and validation.\n\n - Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases.\n\n - Continuously enhances verification infrastructure and flows to improve efficiency and quality.\n\n - Contribute to the evolution of the overall verification methodology and best practices across the organization.\n\nSkills and Qualifications\n\n - Great debugging and problem-solving skills.\n\n - Deep knowledge of SystemVerilog testbench, DPI and UVM.\n\n - Excellent programming skills and knowledge of software engineering practices including object-oriented design.\n\n - Experience developing scalable and portable testbenches and components.\n\n - Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate level simulations.\n\n - Proficient in scripting languages such as Python or Perl.\n\n - Good interpersonal skills and the ability to work as a standout colleague are a must.\n\n - Extremely self-motivated and eager to solve problems\n\n - 10+ years of Design Verification experience.\n\nDesired Skills and Qualifications\n\n - Knowledge of pipelined processor architecture.\n\n - BS or MS in Computer Science or Electrical Engineering.\n\n - 10+ years of hands-on Design Verification experience.\n\nLocation: Sunnyvale, CA\n\nThe base salary range for this position is $250,000 to $300,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications.\n\n \n\nWhy Join Cerebras\n\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\n\n 1. Build a breakthrough AI platform beyond the constraints of the GPU.\n\n 2. Publish and open source their cutting-edge AI research.\n\n 3. Work on one of the fastest AI supercomputers in the world.\n\n 4. Enjoy job stability with startup vitality.\n\n 5. Our simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!\n\nApply today and become part of the forefront of groundbreaking advancements in AI!\n\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\n\nThis website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice."}],"apiVersion":"1"}