At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
About the Role
We’re hiring a leader to build out our BDR function from (almost) zero. It’s a hands-on role that demands a driven builder who is comfortable in real ambiguity: you’ll ship a v1 of the qualification model, outbound motion, and AE handoff, then rewrite it as signal comes in. You're a magnet for talent who loves building and developing a team: recruiting exceptional BDRs, ramping them fast, and making them better every week.
The teams adopting AI are choosing their infrastructure right now, and the motion you create determines how far and how fast Fireworks scales.
Our GTM culture is FIRE:
Face in the place (we sell to developers and ML engineers, and you and your team have to earn the room on inference, latency, and cost);
Industrialize (build the Revenue Factory that powers our Token Factory — instrument everything, treat the pipeline engine as a product);
Rapid (AI infra deals move fast; the motion you build has to be faster);
Engineering Excellence (our buyers are developers, and we match that bar).
You’ll report into our VP of Revenue Marketing and partner closely with Sales, Marketing, and Product.
What You’ll Build
The BDR function from a blank page: the team, the playbook, and the systems behind it
The team itself, from day one. Define the profile, build the interview loop, hire, and ramp while the motion is still forming
An AI-native, instrumented prospecting motion across inbound and outbound, built and iterated like a product
The connective tissue with Marketing and Sales Strategy to convert developer-led demand into enterprise pipeline
Minimum Qualifications
People management experience: you’ve hired, ramped, and coached reps directly
5+ years in GTM roles with 2+ years managing SDR/BDR teams
A track record of generating and scaling pipeline
Has built a function, playbook, or team from scratch
Deep curiosity about AI/ML, you want to be an expert in inference and infrastructure, not just sell it
Hands-on with AI yourself: you actively use tools like Claude Code, Codex, or Cursor to scale your own work, and you'll build a team that does the same
Outstanding verbal and written communication skills
Preferred Qualifications
Experience at an AI/ML, infrastructure, developer-tools, or API-first company, ideally through hypergrowth
Has scaled a BDR team through a Series B-to-C-and-beyond inflection
Hands-on fluency with CRM and sales engagement tooling (Salesforce, Outreach, Apollo) and AI-native prospecting tools
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nAbout the Role\n\nWe’re hiring a leader to build out our BDR function from (almost) zero. It’s a hands-on role that demands a driven builder who is comfortable in real ambiguity: you’ll ship a v1 of the qualification model, outbound motion, and AE handoff, then rewrite it as signal comes in. You're a magnet for talent who loves building and developing a team: recruiting exceptional BDRs, ramping them fast, and making them better every week.\n\nThe teams adopting AI are choosing their infrastructure right now, and the motion you create determines how far and how fast Fireworks scales.\n\nOur GTM culture is FIRE: \n\n - Face in the place (we sell to developers and ML engineers, and you and your team have to earn the room on inference, latency, and cost); \n\n - Industrialize (build the Revenue Factory that powers our Token Factory — instrument everything, treat the pipeline engine as a product); \n\n - Rapid (AI infra deals move fast; the motion you build has to be faster); \n\n - Engineering Excellence (our buyers are developers, and we match that bar).\n\nYou’ll report into our VP of Revenue Marketing and partner closely with Sales, Marketing, and Product.\n\nWhat You’ll Build\n\n - The BDR function from a blank page: the team, the playbook, and the systems behind it\n\n - The team itself, from day one. Define the profile, build the interview loop, hire, and ramp while the motion is still forming\n\n - An AI-native, instrumented prospecting motion across inbound and outbound, built and iterated like a product\n\n - The connective tissue with Marketing and Sales Strategy to convert developer-led demand into enterprise pipeline\n\nMinimum Qualifications\n\n - People management experience: you’ve hired, ramped, and coached reps directly\n\n - 5+ years in GTM roles with 2+ years managing SDR/BDR teams\n\n - A track record of generating and scaling pipeline\n\n - Has built a function, playbook, or team from scratch\n\n - Deep curiosity about AI/ML, you want to be an expert in inference and infrastructure, not just sell it\n\n - Hands-on with AI yourself: you actively use tools like Claude Code, Codex, or Cursor to scale your own work, and you'll build a team that does the same\n\n - Outstanding verbal and written communication skills\n\nPreferred Qualifications\n\n - Experience at an AI/ML, infrastructure, developer-tools, or API-first company, ideally through hypergrowth\n\n - Has scaled a BDR team through a Series B-to-C-and-beyond inflection\n\n - Hands-on fluency with CRM and sales engagement tooling (Salesforce, Outreach, Apollo) and AI-native prospecting tools\n\n \n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"34147044-a771-446e-9bdd-28ae3a6d83d2","title":"MTS, Research Engineer","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-07-08T01:55:35.656+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/34147044-a771-446e-9bdd-28ae3a6d83d2","applyUrl":"https://jobs.ashbyhq.com/fireworks/34147044-a771-446e-9bdd-28ae3a6d83d2/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
About the Role
We are looking for a Research Engineer to join our team, operating at the critical intersection of model research and training infrastructure.
In this role, your time will be split between tackling open-ended research problems—such as designing novel architectures and improving algorithmic efficiency — and building the distributed training systems required to make those research breakthroughs a reality. You won't just be handed a paper to implement; you will be expected to reproduce state-of-the-art results from the literature, identify their limitations, and build the infrastructure needed to push beyond them.
The most significant advances in deep learning require massive scale. We need engineers who are as comfortable reasoning about gradient descent and loss landscapes as they are about distributed systems, GPU cluster utilization, and data pipelines.
What You'll Do
Conduct Open-Ended Research: Explore new model architectures, training objectives, and optimization techniques. Formulate hypotheses, design experiments, and iterate quickly based on empirical results.
Reproduce and Extend State-of-the-Art: Implement and reproduce results from recent machine learning papers. Identify bottlenecks, propose improvements, and scale these methods to larger datasets and models.
Build and Scale Training Infrastructure: Design, implement, and maintain high-performance, distributed machine learning systems. Optimize training loops, data loaders, and communication overhead across large GPU clusters.
Bridge Science and Engineering: Translate abstract mathematical concepts and research ideas into robust, bug-free, and efficient code.
Collaborate Cross-Functionally: Work closely with Research Scientists to unblock their experiments by providing tooling, optimizing code, and co-designing experiments that are hardware-aware.
We Expect You To Have:
Strong programming skills (Python, C++, or Rust) and a commitment to writing clean, maintainable code.
Deep practical knowledge of machine learning frameworks (PyTorch, JAX, or TensorFlow).
Experience working with large distributed systems and parallel computing (e.g., CUDA, NCCL, MPI).
A strong foundation in linear algebra, calculus, probability, and statistics.
A proven track record of implementing complex deep learning algorithms from scratch.
Nice to Have:
A Master’s or PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related field (or equivalent industry experience).
Experience with low-level GPU programming (CUDA/Triton) or hardware co-design.
Familiarity with the challenges of training Large Language Models (LLMs)
Familiarity with the challenges of inference, and OSS inference engines such as SGLang and vLLM
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nAbout the Role\n\nWe are looking for a Research Engineer to join our team, operating at the critical intersection of model research and training infrastructure.\n\nIn this role, your time will be split between tackling open-ended research problems—such as designing novel architectures and improving algorithmic efficiency — and building the distributed training systems required to make those research breakthroughs a reality. You won't just be handed a paper to implement; you will be expected to reproduce state-of-the-art results from the literature, identify their limitations, and build the infrastructure needed to push beyond them.\n\nThe most significant advances in deep learning require massive scale. We need engineers who are as comfortable reasoning about gradient descent and loss landscapes as they are about distributed systems, GPU cluster utilization, and data pipelines.\n\n\n \n\nWhat You'll Do\n\n - Conduct Open-Ended Research: Explore new model architectures, training objectives, and optimization techniques. Formulate hypotheses, design experiments, and iterate quickly based on empirical results.\n\n - Reproduce and Extend State-of-the-Art: Implement and reproduce results from recent machine learning papers. Identify bottlenecks, propose improvements, and scale these methods to larger datasets and models.\n\n - Build and Scale Training Infrastructure: Design, implement, and maintain high-performance, distributed machine learning systems. Optimize training loops, data loaders, and communication overhead across large GPU clusters.\n\n - Bridge Science and Engineering: Translate abstract mathematical concepts and research ideas into robust, bug-free, and efficient code.\n\n - Collaborate Cross-Functionally: Work closely with Research Scientists to unblock their experiments by providing tooling, optimizing code, and co-designing experiments that are hardware-aware.\n\nWe Expect You To Have:\n\n - Strong programming skills (Python, C++, or Rust) and a commitment to writing clean, maintainable code.\n\n - Deep practical knowledge of machine learning frameworks (PyTorch, JAX, or TensorFlow).\n\n - Experience working with large distributed systems and parallel computing (e.g., CUDA, NCCL, MPI).\n\n - A strong foundation in linear algebra, calculus, probability, and statistics.\n\n - A proven track record of implementing complex deep learning algorithms from scratch.\n\nNice to Have:\n\n - A Master’s or PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related field (or equivalent industry experience).\n\n - Experience with low-level GPU programming (CUDA/Triton) or hardware co-design.\n\n - Familiarity with the challenges of training Large Language Models (LLMs)\n\n - Familiarity with the challenges of inference, and OSS inference engines such as SGLang and vLLM\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"f38678eb-77d3-42f4-90aa-f24da0a0e929","title":"Senior GRC Specialist","department":"G&A","team":"G&A","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-07-06T17:07:17.234+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/f38678eb-77d3-42f4-90aa-f24da0a0e929","applyUrl":"https://jobs.ashbyhq.com/fireworks/f38678eb-77d3-42f4-90aa-f24da0a0e929/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
About the role
We're looking for a GRC Specialist to join our security and compliance team. You'll help us mature our compliance program across frameworks like SOC 2, HIPAA, ISO 27001, ISO 27701, ISO 42001, and GDPR - supporting audits, managing risk, and partnering with engineering and operations teams to keep our controls effective as we scale. From day one you'll own operational cornerstones of our program, including user access reviews, our security awareness program through the Adaptive Security platform, and third-party risk management, with room to grow into broader audit and program leadership over time. This is a great fit for someone with a foundation in security or compliance who's ready to take ownership of meaningful work in a fast-moving SaaS environment.
What you'll do
Own day-to-day GRC operations - including (but not limited to) user access reviews and certifications, security awareness and phishing/deepfake simulation facilitation, JML tracking, and triage and enforcement of policy and control exceptions.
Run the risk management program - perform annual and ad-hoc risk assessments, maintain the risk register, partner with risk owners on remediation, and track issues through to closure.
Manage third-party risk - run vendor and subprocessor risk assessments, conduct ongoing monitoring, and track remediation across our critical vendors.
Design and execute targeted internal audits to test control effectiveness, and facilitate or support external audit cycles by coordinating evidence, control owners, and remediation.
Own continuous control monitoring and evidence automation - administer our GRC platform, keep automated control tests and evidence healthy, and maintain audit readiness year-round rather than point-in-time.
Build and foster relationships with cross-functional partners across engineering, IT, operations, legal, and sales - meeting teams where they are rather than gatekeeping.
Partner with control owners to educate them on their control responsibilities, ownership, and expectations; prepare them for audits; and help them operationalize controls rather than treat compliance as a checkbox.
Keep the policy library current - review and update security policies, standards, and procedures so they stay practical and aligned to the frameworks we operate under.
Turn program data into action - translate access review, awareness, and risk findings into insights and metrics that flag high-risk users, teams, or behaviors, report to leadership, and drive targeted interventions.
Take on additional GRC projects as the program evolves; we're a growing team and priorities shift.
How the role will grow
As you build context on our environment and program, you'll take on broader ownership across third-party risk, audit leadership, and program maturity:
End-to-end audit leadership - move from supporting audits to owning them: scoping, auditor coordination, and driving the cycle to completion across frameworks.
Program and control maturity - lead control improvement and automation initiatives that raise the bar on how efficiently we run the program as we scale.
Leadership and influence - mentor newer team members, represent GRC in cross-functional projects, and help shape the direction of the program.
What we're looking for
5-7 years of experience in GRC, IT audit, information security, or a closely related field
Working knowledge of major security and privacy frameworks such as SOC 2, ISO 27001/27701/42001, NIST CSF, HIPAA, GDPR, or CCPA
Experience with GRC platforms (Anecdotes, Vanta, Drata, Secureframe, OneTrust, ServiceNow GRC)
Experience running user access reviews and a solid understanding of identity and access management concepts (RBAC, least privilege, segregation of duties, JML processes)
Hands-on experience administering a security awareness or phishing simulation platform (Adaptive Security, KnowBe4, Hoxhunt, Proofpoint, or similar)
Comfort with cloud environments (AWS, GCP, or Azure) and how SaaS products are built and operated
Strong written communication; you can translate control requirements and security concepts into language engineers, customers, and non-technical employees understand
Detail-oriented and organized, with the ability to juggle multiple audits, campaigns, and deadlines
A collaborative mindset; you enjoy working across teams rather than gatekeeping
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nAbout the role\n\nWe're looking for a GRC Specialist to join our security and compliance team. You'll help us mature our compliance program across frameworks like SOC 2, HIPAA, ISO 27001, ISO 27701, ISO 42001, and GDPR - supporting audits, managing risk, and partnering with engineering and operations teams to keep our controls effective as we scale. From day one you'll own operational cornerstones of our program, including user access reviews, our security awareness program through the Adaptive Security platform, and third-party risk management, with room to grow into broader audit and program leadership over time. This is a great fit for someone with a foundation in security or compliance who's ready to take ownership of meaningful work in a fast-moving SaaS environment.\n\nWhat you'll do\n\n - Own day-to-day GRC operations - including (but not limited to) user access reviews and certifications, security awareness and phishing/deepfake simulation facilitation, JML tracking, and triage and enforcement of policy and control exceptions.\n\n - Run the risk management program - perform annual and ad-hoc risk assessments, maintain the risk register, partner with risk owners on remediation, and track issues through to closure.\n\n - Manage third-party risk - run vendor and subprocessor risk assessments, conduct ongoing monitoring, and track remediation across our critical vendors.\n\n - Design and execute targeted internal audits to test control effectiveness, and facilitate or support external audit cycles by coordinating evidence, control owners, and remediation.\n\n - Own continuous control monitoring and evidence automation - administer our GRC platform, keep automated control tests and evidence healthy, and maintain audit readiness year-round rather than point-in-time.\n\n - Build and foster relationships with cross-functional partners across engineering, IT, operations, legal, and sales - meeting teams where they are rather than gatekeeping.\n\n - Partner with control owners to educate them on their control responsibilities, ownership, and expectations; prepare them for audits; and help them operationalize controls rather than treat compliance as a checkbox.\n\n - Keep the policy library current - review and update security policies, standards, and procedures so they stay practical and aligned to the frameworks we operate under.\n\n - Turn program data into action - translate access review, awareness, and risk findings into insights and metrics that flag high-risk users, teams, or behaviors, report to leadership, and drive targeted interventions.\n\n - Take on additional GRC projects as the program evolves; we're a growing team and priorities shift.\n\nHow the role will grow\n\nAs you build context on our environment and program, you'll take on broader ownership across third-party risk, audit leadership, and program maturity:\n\n - End-to-end audit leadership - move from supporting audits to owning them: scoping, auditor coordination, and driving the cycle to completion across frameworks.\n\n - Program and control maturity - lead control improvement and automation initiatives that raise the bar on how efficiently we run the program as we scale.\n\n - Leadership and influence - mentor newer team members, represent GRC in cross-functional projects, and help shape the direction of the program.\n\nWhat we're looking for\n\n - 5-7 years of experience in GRC, IT audit, information security, or a closely related field\n\n - Working knowledge of major security and privacy frameworks such as SOC 2, ISO 27001/27701/42001, NIST CSF, HIPAA, GDPR, or CCPA\n\n - Experience with GRC platforms (Anecdotes, Vanta, Drata, Secureframe, OneTrust, ServiceNow GRC)\n\n - Experience running user access reviews and a solid understanding of identity and access management concepts (RBAC, least privilege, segregation of duties, JML processes)\n\n - Hands-on experience administering a security awareness or phishing simulation platform (Adaptive Security, KnowBe4, Hoxhunt, Proofpoint, or similar)\n\n - Comfort with cloud environments (AWS, GCP, or Azure) and how SaaS products are built and operated\n\n - Strong written communication; you can translate control requirements and security concepts into language engineers, customers, and non-technical employees understand\n\n - Detail-oriented and organized, with the ability to juggle multiple audits, campaigns, and deadlines\n\n - A collaborative mindset; you enjoy working across teams rather than gatekeeping\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"3af80f2c-ee2f-442a-b921-6529aaef49d9","title":"Microsoft Partner Sales Manager","department":"Go To Market","team":"Partnerships","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-26T00:37:48.226+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/3af80f2c-ee2f-442a-b921-6529aaef49d9","applyUrl":"https://jobs.ashbyhq.com/fireworks/3af80f2c-ee2f-442a-b921-6529aaef49d9/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We're hiring a high-ownership sales operator to drive sourced pipeline and revenue through the Microsoft Azure channel.
This is a quota-carrying, field-facing role. You'll map Microsoft's ISV and enterprise field org, activate co-sell motions with the right PDMs and AEs, and build the repeatable sales plays that move customers to Fireworks AI through Azure Foundry. You'll own the forecast and the number.
The playbook doesn't fully exist yet. You'll have real influence over how we engage Microsoft's field teams, what good looks like for partner-sourced pipeline, and how we build a co-sell motion that scales across ISV and enterprise segments. If you thrive when you're creating from scratch and can hold yourself accountable to a number while doing it, this is the role.
Pipeline and revenue
Source and own a pipeline target through the Microsoft Azure channel
Co-sell qualified opportunities with Microsoft ISV and enterprise AEs and PDMs
Run weekly forecasting cadences with accurate CRM hygiene and clear escalation visibility
Team mapping and stakeholder management
Build and maintain a living map of Microsoft's field org across ISV and enterprise-facing teams - who owns which accounts, who moves deals, who has co-sell budget
Develop working relationships with PDMs, field AEs, and ISV partner managers at Microsoft
Serve as Fireworks AI's primary point of contact for joint business reviews, pipeline reviews, and co-sell coordination
Sales plays and enablement
Develop sales plays tailored to the ISV and enterprise motion - positioning Fireworks AI's inference platform against the decision criteria that matter in each segment
Build and deliver enablement for Microsoft field sellers on Fireworks AI: clear, crisp positioning they can use in front of customers without a technical translator
Design the intake, escalation, and co-sell workflows that keep deals from stalling
Joint planning and operations
Own joint business planning with Microsoft counterparts: territory plans, account maps, co-sell targets, and QBR cadences
Coordinate co-marketing moments (joint events, solution briefs, field plays) that generate ISV and enterprise pipeline
Surface field intelligence from Microsoft conversations back to Fireworks AI's product and GTM teams
Have 7+ years in GTM, partnerships, or field sales at a technology company - and a track record of operating fast when the environment changes
Know how Microsoft's field org actually works: account teams, SSPs, GBBs, marketplace mechanics, co-sell programs, MACC spend, partner incentives - and how to activate them at the deal level
Build systems, not just run plays. You document the motion, create the playbooks, and make it repeatable
Are comfortable owning a number before all the conditions are perfect, and stay accountable on pipeline sourcing, progression, forecasting
Can communicate clearly and concisely - you translate complex platform capabilities into a value story a non-technical field seller can use in front of a customer
Hold yourself accountable to pipeline hygiene and forecast accuracy - not just relationship depth
This is not an engineering role. But it requires genuine curiosity about how AI inference platforms work.
You'll need working fluency in model serving, inference optimization, and AI training infrastructure - enough to speak credibly about why Fireworks AI's platform matters to ISVs and enterprises evaluating options in the market. If you don't have that fluency today, you can build it here - we'll help. What you can't be is someone who deflects every technical question or can't hold a credible 30-minute conversation with a solutions architect or a technical evaluator.
The through-line: you need to understand what we do well enough to translate it for someone who doesn't. That's the bar.
Experience working at or within a hyperscaler partner ecosystem (Microsoft, AWS, GCP)
Experience selling or partnering in AI/ML infrastructure, model serving, or MLOps
Experience working with ISVs at the platform layer - understanding their build-vs-buy decisions and procurement dynamics
Non-linear career path - varied, scrappy backgrounds carry real weight here
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nABOUT THE ROLE\n\nWe're hiring a high-ownership sales operator to drive sourced pipeline and revenue through the Microsoft Azure channel.\n\nThis is a quota-carrying, field-facing role. You'll map Microsoft's ISV and enterprise field org, activate co-sell motions with the right PDMs and AEs, and build the repeatable sales plays that move customers to Fireworks AI through Azure Foundry. You'll own the forecast and the number.\n\nThe playbook doesn't fully exist yet. You'll have real influence over how we engage Microsoft's field teams, what good looks like for partner-sourced pipeline, and how we build a co-sell motion that scales across ISV and enterprise segments. If you thrive when you're creating from scratch and can hold yourself accountable to a number while doing it, this is the role.\n\n\nWHAT YOU'LL OWN\n\nPipeline and revenue\n\n - Source and own a pipeline target through the Microsoft Azure channel\n\n - Co-sell qualified opportunities with Microsoft ISV and enterprise AEs and PDMs\n\n - Run weekly forecasting cadences with accurate CRM hygiene and clear escalation visibility\n\nTeam mapping and stakeholder management\n\n - Build and maintain a living map of Microsoft's field org across ISV and enterprise-facing teams - who owns which accounts, who moves deals, who has co-sell budget\n\n - Develop working relationships with PDMs, field AEs, and ISV partner managers at Microsoft\n\n - Serve as Fireworks AI's primary point of contact for joint business reviews, pipeline reviews, and co-sell coordination\n\nSales plays and enablement\n\n - Develop sales plays tailored to the ISV and enterprise motion - positioning Fireworks AI's inference platform against the decision criteria that matter in each segment\n\n - Build and deliver enablement for Microsoft field sellers on Fireworks AI: clear, crisp positioning they can use in front of customers without a technical translator\n\n - Design the intake, escalation, and co-sell workflows that keep deals from stalling\n\nJoint planning and operations\n\n - Own joint business planning with Microsoft counterparts: territory plans, account maps, co-sell targets, and QBR cadences\n\n - Coordinate co-marketing moments (joint events, solution briefs, field plays) that generate ISV and enterprise pipeline\n\n - Surface field intelligence from Microsoft conversations back to Fireworks AI's product and GTM teams\n\n\nYOU'RE A GOOD FIT IF YOU\n\n - Have 7+ years in GTM, partnerships, or field sales at a technology company - and a track record of operating fast when the environment changes\n\n - Know how Microsoft's field org actually works: account teams, SSPs, GBBs, marketplace mechanics, co-sell programs, MACC spend, partner incentives - and how to activate them at the deal level\n\n - Build systems, not just run plays. You document the motion, create the playbooks, and make it repeatable\n\n - Are comfortable owning a number before all the conditions are perfect, and stay accountable on pipeline sourcing, progression, forecasting\n\n - Can communicate clearly and concisely - you translate complex platform capabilities into a value story a non-technical field seller can use in front of a customer\n\n - Hold yourself accountable to pipeline hygiene and forecast accuracy - not just relationship depth\n\n\nTHE TECHNICAL BAR\n\nThis is not an engineering role. But it requires genuine curiosity about how AI inference platforms work.\n\nYou'll need working fluency in model serving, inference optimization, and AI training infrastructure - enough to speak credibly about why Fireworks AI's platform matters to ISVs and enterprises evaluating options in the market. If you don't have that fluency today, you can build it here - we'll help. What you can't be is someone who deflects every technical question or can't hold a credible 30-minute conversation with a solutions architect or a technical evaluator.\n\nThe through-line: you need to understand what we do well enough to translate it for someone who doesn't. That's the bar.\n\n\nNICE TO HAVE\n\n - Experience working at or within a hyperscaler partner ecosystem (Microsoft, AWS, GCP)\n\n - Experience selling or partnering in AI/ML infrastructure, model serving, or MLOps\n\n - Experience working with ISVs at the platform layer - understanding their build-vs-buy decisions and procurement dynamics\n\n - Non-linear career path - varied, scrappy backgrounds carry real weight here\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"2393546c-ef71-4054-8c75-4f16caeffc5b","title":"Executive Assistant","department":"G&A","team":"G&A","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-07-26T20:40:12.208+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/2393546c-ef71-4054-8c75-4f16caeffc5b","applyUrl":"https://jobs.ashbyhq.com/fireworks/2393546c-ef71-4054-8c75-4f16caeffc5b/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We are looking for a highly organized, proactive, and detail-oriented Executive Assistant to support our senior leadership team. This is a high-trust, high-autonomy role for someone who operates with discretion, moves fast, and takes genuine ownership of keeping leadership effective and well-prepared. The ideal candidate is not just an organizer — they're a thoughtful partner and a trusted confidant. You'll be the connective tissue between our executives and the world around them, bringing sound judgment and a calm, professional presence to everything you do. This role may support other executives as needed.
Main Responsibilities
Calendar & Schedule Management: Manage complex, multi-executive schedules. Strategically prioritize and protect time in alignment with business objectives.
Communication & Correspondence: Own the executive inbox. Triage, prioritize, and respond on their behalf — redirecting vendors and external requests with warmth and professionalism. Draft responses and correspondence as needed.
Meeting Support: Ensure executives begin each day fully prepared: briefing notes, meeting context, open action items, and anything they need to walk in sharp. Prepare agendas and follow up on action items as needed.
Travel Coordination: Organize domestic and international travel end-to-end: flights, accommodation, ground transport, detailed itineraries, and expense reporting.
Confidential Support: Manage sensitive and confidential information with the utmost discretion and integrity.
Project Management: Support strategic projects, internal initiatives, and ad hoc research tasks. Able to pick up a thread and run with it independently.
Liaison Role: Serve as the primary point of contact between executives and internal/external stakeholders. Build relationships and stay attuned to what's happening on the ground.
Additional Administrative Support: Complete expense reports, handle personal tasks as needed, and support other executives as needed.
Preferred Attributes
Background in a fast-paced environment — finance, technology, AI, or startups preferred
Clear, upfront communicator — comfortable navigating ambiguity with confidence and composure
Meticulous attention to detail, especially across scheduling and travel; able to prioritize effectively in high-pressure environments
Strong written and verbal communication skills; professional and warm in every context
Strong interpersonal relationships — a natural relationship-builder who earns trust quickly across all levels of an organization
Good judgment — knows when to act independently and when to loop in
Tech-savvy and comfortable with modern productivity tools
Familiarity with AI tools or workflow automation — able to help build and maintain systems that reduce manual lift
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nWe are looking for a highly organized, proactive, and detail-oriented Executive Assistant to support our senior leadership team. This is a high-trust, high-autonomy role for someone who operates with discretion, moves fast, and takes genuine ownership of keeping leadership effective and well-prepared. The ideal candidate is not just an organizer — they're a thoughtful partner and a trusted confidant. You'll be the connective tissue between our executives and the world around them, bringing sound judgment and a calm, professional presence to everything you do. This role may support other executives as needed.\n\n \n\nMain Responsibilities\n\n - Calendar & Schedule Management: Manage complex, multi-executive schedules. Strategically prioritize and protect time in alignment with business objectives.\n\n - Communication & Correspondence: Own the executive inbox. Triage, prioritize, and respond on their behalf — redirecting vendors and external requests with warmth and professionalism. Draft responses and correspondence as needed.\n\n - Meeting Support: Ensure executives begin each day fully prepared: briefing notes, meeting context, open action items, and anything they need to walk in sharp. Prepare agendas and follow up on action items as needed.\n\n - Travel Coordination: Organize domestic and international travel end-to-end: flights, accommodation, ground transport, detailed itineraries, and expense reporting.\n\n - Confidential Support: Manage sensitive and confidential information with the utmost discretion and integrity.\n\n - Project Management: Support strategic projects, internal initiatives, and ad hoc research tasks. Able to pick up a thread and run with it independently.\n\n - Liaison Role: Serve as the primary point of contact between executives and internal/external stakeholders. Build relationships and stay attuned to what's happening on the ground.\n\n - Additional Administrative Support: Complete expense reports, handle personal tasks as needed, and support other executives as needed.\n\n \n\nPreferred Attributes\n\n - Background in a fast-paced environment — finance, technology, AI, or startups preferred\n\n - Clear, upfront communicator — comfortable navigating ambiguity with confidence and composure\n\n - Meticulous attention to detail, especially across scheduling and travel; able to prioritize effectively in high-pressure environments\n\n - Strong written and verbal communication skills; professional and warm in every context\n\n - Strong interpersonal relationships — a natural relationship-builder who earns trust quickly across all levels of an organization\n\n - Good judgment — knows when to act independently and when to loop in\n\n - Tech-savvy and comfortable with modern productivity tools\n\n - Familiarity with AI tools or workflow automation — able to help build and maintain systems that reduce manual lift \n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"85e542b8-6349-48a7-b1b4-3818baf945aa","title":"Enterprise Account Executive","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-05T23:21:22.835+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/85e542b8-6349-48a7-b1b4-3818baf945aa","applyUrl":"https://jobs.ashbyhq.com/fireworks/85e542b8-6349-48a7-b1b4-3818baf945aa/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We are seeking an experienced Enterprise Account Executive to join our sales team. The ideal candidate has a solid track record at early-stage startups, selling to technical stakeholders, and consistently exceeding quotas by closing six-figure deals. This role demands a driven individual capable of navigating the complexities of selling software solutions to large enterprises, with a keen understanding of the technical nuances involved.
Drive new business opportunities by developing and executing a sales strategy for selling Fireworks AI within targeted accounts
Gain a deep understanding of Fireworks AI's offerings and value proposition, effectively articulating them in the market
Focus on pipeline generation within your targeted accounts to ensure long-term success
Interact with and leverage the Channel and Alliance partner community to find new opportunities and drive existing deals to close
Manage the entire sales cycle from prospecting to procurement
Forecast accurately and leverage internal resources to hit your annual quota efficiently
Regularly update all active accounts, reporting on sales activities, status, and progress
Maintain a high level of customer satisfaction and referenceability
Travel for client visits and presentations as needed
Bachelor’s degree or 8-12+ years of working experience; 6+ years of progressive SaaS software sales experience, with a proven \"hunter\" mentality; 4+ years experience selling SaaS products to a technical audience
Demonstrated success in closing business in large complex enterprise accounts
Excellent negotiation, analytical, financial, and organizational skills, thriving in an evolving entrepreneurial environment
Outstanding verbal and written communication skills
Fireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in the San Francisco Bay Area for this role is $300,000 - $330,000 per year.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nWe are seeking an experienced Enterprise Account Executive to join our sales team. The ideal candidate has a solid track record at early-stage startups, selling to technical stakeholders, and consistently exceeding quotas by closing six-figure deals. This role demands a driven individual capable of navigating the complexities of selling software solutions to large enterprises, with a keen understanding of the technical nuances involved.\n\n\nKEY RESPONSIBILITIES:\n\n - Drive new business opportunities by developing and executing a sales strategy for selling Fireworks AI within targeted accounts\n\n - Gain a deep understanding of Fireworks AI's offerings and value proposition, effectively articulating them in the market\n\n - Focus on pipeline generation within your targeted accounts to ensure long-term success\n\n - Interact with and leverage the Channel and Alliance partner community to find new opportunities and drive existing deals to close\n\n - Manage the entire sales cycle from prospecting to procurement\n\n - Forecast accurately and leverage internal resources to hit your annual quota efficiently\n\n - Regularly update all active accounts, reporting on sales activities, status, and progress\n\n - Maintain a high level of customer satisfaction and referenceability\n\n - Travel for client visits and presentations as needed\n\n\nMINIMUM REQUIREMENTS:\n\n - Bachelor’s degree or 8-12+ years of working experience; 6+ years of progressive SaaS software sales experience, with a proven \"hunter\" mentality; 4+ years experience selling SaaS products to a technical audience\n\n - Demonstrated success in closing business in large complex enterprise accounts\n\n - Excellent negotiation, analytical, financial, and organizational skills, thriving in an evolving entrepreneurial environment\n\n - Outstanding verbal and written communication skills\n\nFireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in the San Francisco Bay Area for this role is $300,000 - $330,000 per year.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"93faf385-9322-4172-8ef2-42a9a6c889e6","title":"Member of Technical Staff, Cloud Infrastructure, Singapore","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"Singapore","secondaryLocations":[],"publishedAt":"2026-06-24T06:16:41.707+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Singapore","addressCountry":"Singapore","addressLocality":"Singapore"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/93faf385-9322-4172-8ef2-42a9a6c889e6","applyUrl":"https://jobs.ashbyhq.com/fireworks/93faf385-9322-4172-8ef2-42a9a6c889e6/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
Here at Fireworks, we’re building the future of generative AI infrastructure. Fireworks offers the generative AI platform with the highest-quality models and the fastest, most scalable inference. We’ve been independently benchmarked to have the fastest LLM inference and have been getting great traction with innovative research projects, like our own function calling and multi-modal models. Fireworks is funded by top investors, like Benchmark and Sequoia, and we’re an ambitious, fun team composed primarily of veterans from Pytorch and Google Vertex AI.
As a Backend Software Engineer, you’ll be responsible for designing and developing the core backend systems that power Fireworks AI’s high-performance generative AI platform. Your work will focus on ensuring efficiency, scalability, and stability in handling AI workloads.
Design and build core backend software components, ensuring efficiency, scalability, and stability of system resources
Conduct design/code reviews and collaborate with cross-functional teams
Continuously analyze and optimize infrastructure efficiency for AI workloads (compute, storage, networking)
Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
3+ years experience working in ML infra (PyTorch, Vertex AI, Sagemaker, etc.)
Experience building, scaling, and optimizing enterprise-grade Machine Learning systems
Experience in AI or large scale infrastructure
Master’s or PhD degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nABOUT US:\n\nHere at Fireworks, we’re building the future of generative AI infrastructure. Fireworks offers the generative AI platform with the highest-quality models and the fastest, most scalable inference. We’ve been independently benchmarked to have the fastest LLM inference and have been getting great traction with innovative research projects, like our own function calling and multi-modal models. Fireworks is funded by top investors, like Benchmark and Sequoia, and we’re an ambitious, fun team composed primarily of veterans from Pytorch and Google Vertex AI.\n\n\nTHE ROLE:\n\nAs a Backend Software Engineer, you’ll be responsible for designing and developing the core backend systems that power Fireworks AI’s high-performance generative AI platform. Your work will focus on ensuring efficiency, scalability, and stability in handling AI workloads.\n\n\nKEY RESPONSIBILITIES:\n\n - Design and build core backend software components, ensuring efficiency, scalability, and stability of system resources\n\n - Conduct design/code reviews and collaborate with cross-functional teams\n\n - Continuously analyze and optimize infrastructure efficiency for AI workloads (compute, storage, networking)\n\n\nMINIMUM QUALIFICATIONS:\n\n - Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience\n\n - 3+ years experience working in ML infra (PyTorch, Vertex AI, Sagemaker, etc.)\n\n - Experience building, scaling, and optimizing enterprise-grade Machine Learning systems\n\n\nPREFERRED QUALIFICATIONS:\n\n - Experience in AI or large scale infrastructure\n\n - Master’s or PhD degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\n \n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"2facf9c7-9d73-4828-bbab-8adc37708f4c","title":"Enterprise Account Executive, EMEA","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"London","secondaryLocations":[],"publishedAt":"2026-07-22T22:22:36.872+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"London","addressCountry":"United Kingdom","addressLocality":"London"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/2facf9c7-9d73-4828-bbab-8adc37708f4c","applyUrl":"https://jobs.ashbyhq.com/fireworks/2facf9c7-9d73-4828-bbab-8adc37708f4c/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We are seeking an experienced Enterprise Account Executive to join our sales team. The ideal candidate has a solid track record at early-stage startups, selling to technical stakeholders, and consistently exceeding quotas by closing six-figure deals. This role demands a driven individual capable of navigating the complexities of selling software solutions to large enterprises, with a keen understanding of the technical nuances involved.
Drive new business opportunities by developing and executing a sales strategy for selling Fireworks AI within targeted accounts
Gain a deep understanding of Fireworks AI's offerings and value proposition, effectively articulating them in the market
Focus on pipeline generation within your targeted accounts to ensure long-term success
Interact with and leverage the Channel and Alliance partner community to find new opportunities and drive existing deals to close
Manage the entire sales cycle from prospecting to procurement
Forecast accurately and leverage internal resources to hit your annual quota efficiently
Regularly update all active accounts, reporting on sales activities, status, and progress
Maintain a high level of customer satisfaction and referenceability
Travel for client visits and presentations as needed
Bachelor’s degree or equivalent years of working experience
5+ years of progressive SaaS software sales experience, with a proven \"hunter\" mentality
2+ years experience selling SaaS products to a technical audience
Demonstrated success in closing business in large complex enterprise accounts
Excellent negotiation, analytical, financial, and organizational skills, thriving in an evolving entrepreneurial environment
Outstanding verbal and written communication skills
Fireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in London, UK for this role is £200,000 - £240,000 per year.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nWe are seeking an experienced Enterprise Account Executive to join our sales team. The ideal candidate has a solid track record at early-stage startups, selling to technical stakeholders, and consistently exceeding quotas by closing six-figure deals. This role demands a driven individual capable of navigating the complexities of selling software solutions to large enterprises, with a keen understanding of the technical nuances involved.\n\n\nKEY RESPONSIBILITIES:\n\n - Drive new business opportunities by developing and executing a sales strategy for selling Fireworks AI within targeted accounts\n\n - Gain a deep understanding of Fireworks AI's offerings and value proposition, effectively articulating them in the market\n\n - Focus on pipeline generation within your targeted accounts to ensure long-term success\n\n - Interact with and leverage the Channel and Alliance partner community to find new opportunities and drive existing deals to close\n\n - Manage the entire sales cycle from prospecting to procurement\n\n - Forecast accurately and leverage internal resources to hit your annual quota efficiently\n\n - Regularly update all active accounts, reporting on sales activities, status, and progress\n\n - Maintain a high level of customer satisfaction and referenceability\n\n - Travel for client visits and presentations as needed\n\n\nMINIMUM REQUIREMENTS:\n\n - Bachelor’s degree or equivalent years of working experience \n\n - 5+ years of progressive SaaS software sales experience, with a proven \"hunter\" mentality\n\n - 2+ years experience selling SaaS products to a technical audience\n\n - Demonstrated success in closing business in large complex enterprise accounts\n\n - Excellent negotiation, analytical, financial, and organizational skills, thriving in an evolving entrepreneurial environment\n\n - Outstanding verbal and written communication skills\n\nFireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in London, UK for this role is £200,000 - £240,000 per year.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"044b1823-7d0d-4da2-b265-676f2a5a50c3","title":"Applied Machine Learning Engineer, Singapore","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"Singapore","secondaryLocations":[],"publishedAt":"2026-07-23T01:53:02.276+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Singapore","addressCountry":"Singapore","addressLocality":"Singapore"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/044b1823-7d0d-4da2-b265-676f2a5a50c3","applyUrl":"https://jobs.ashbyhq.com/fireworks/044b1823-7d0d-4da2-b265-676f2a5a50c3/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.
Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.
Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.
Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.
New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.
Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.
Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.
Bachelor’s degree in Computer Science, Engineering, or a related technical field.
5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.
Robust coding skills required, preferably with proficiency in Python.
Demonstrated ability to lead and execute complex technical projects with a focus on customer success.
Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.
Master’s degree in Computer Science, Engineering, or a related technical field.
Experience working in a startup or fast-paced environment.
Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).
Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nAs an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.\n\n\nKEY RESPONSIBILITIES:\n\n - Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.\n\n - Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.\n\n - Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.\n\n - Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.\n\n - New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.\n\n - Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.\n\n - Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.\n\n\nMINIMUM QUALIFICATIONS:\n\n - Bachelor’s degree in Computer Science, Engineering, or a related technical field.\n\n - 5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.\n\n - Robust coding skills required, preferably with proficiency in Python.\n\n - Demonstrated ability to lead and execute complex technical projects with a focus on customer success.\n\n - Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.\n\n\nPREFERRED QUALIFICATIONS:\n\n - Master’s degree in Computer Science, Engineering, or a related technical field.\n\n - Experience working in a startup or fast-paced environment.\n\n - Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).\n\n - Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"ee35bd97-43f9-4574-8ab7-81debd5d3d1a","title":"Member of Technical Staff, Research","department":"Engineering","team":"Research","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2025-04-17T21:47:41.078+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/ee35bd97-43f9-4574-8ab7-81debd5d3d1a","applyUrl":"https://jobs.ashbyhq.com/fireworks/ee35bd97-43f9-4574-8ab7-81debd5d3d1a/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
As a Member of Technical Staff on the Research team, you’ll push the boundaries of generative AI, advancing LLMs and multimodal systems through foundational research. Your work will enhance model efficiency, accuracy, and scalability, directly shaping our high-performance AI infrastructure. You'll collaborate with top experts in deep learning, distributed systems, and optimization to bring cutting-edge research into real-world applications. You'll also have the opportunity to shape how some of the world’s leading companies build and deploy AI through the models and tools you help create.
Conduct foundational research to advance the capabilities, efficiency, and reliability of LLMs and multimodal systems
Design, implement, and evaluate novel model architectures, training methods, and optimization techniques
Collaborate with engineering teams to transition research prototypes into production-grade systems
Analyze empirical results, identify performance bottlenecks, and iterate quickly to improve model quality
Contribute to internal research strategy by identifying high-impact opportunities and emerging trends in AI
Research background in Artificial Intelligence, Machine Learning, Physics, or similar field
Experience solving analytical problems using analytic and quantitative approaches
Experience communicating research to audiences with different backgrounds
Experience coding in C/C++, Python, or other similar languages
PhD degree in Computer Science, Computational Physics, Mathematics, or a similar field
Research and engineering experience demonstrated via grants, fellowships, patents, internships, work experience, and/or coding competitions
Experience having first-authored publications at peer-reviewed conferences or journals
Experience working with ML frameworks such as PyTorch, TensorFlow, or Jax
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nAs a Member of Technical Staff on the Research team, you’ll push the boundaries of generative AI, advancing LLMs and multimodal systems through foundational research. Your work will enhance model efficiency, accuracy, and scalability, directly shaping our high-performance AI infrastructure. You'll collaborate with top experts in deep learning, distributed systems, and optimization to bring cutting-edge research into real-world applications. You'll also have the opportunity to shape how some of the world’s leading companies build and deploy AI through the models and tools you help create.\n\n\nKEY RESPONSIBILITIES\n\n - Conduct foundational research to advance the capabilities, efficiency, and reliability of LLMs and multimodal systems\n\n - Design, implement, and evaluate novel model architectures, training methods, and optimization techniques\n\n - Collaborate with engineering teams to transition research prototypes into production-grade systems\n\n - Analyze empirical results, identify performance bottlenecks, and iterate quickly to improve model quality\n\n - Contribute to internal research strategy by identifying high-impact opportunities and emerging trends in AI\n\n\nMINIMUM QUALIFICATIONS:\n\n - Research background in Artificial Intelligence, Machine Learning, Physics, or similar field\n\n - Experience solving analytical problems using analytic and quantitative approaches\n\n - Experience communicating research to audiences with different backgrounds\n\n - Experience coding in C/C++, Python, or other similar languages\n\n\nPREFERRED QUALIFICATIONS:\n\n - PhD degree in Computer Science, Computational Physics, Mathematics, or a similar field\n\n - Research and engineering experience demonstrated via grants, fellowships, patents, internships, work experience, and/or coding competitions\n\n - Experience having first-authored publications at peer-reviewed conferences or journals\n\n - Experience working with ML frameworks such as PyTorch, TensorFlow, or Jax\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"a2850702-dea3-4e2c-a3ec-7ae257d36eb7","title":"Member of Technical Staff, AI Training Infrastructure","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2025-04-21T20:14:41.838+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/a2850702-dea3-4e2c-a3ec-7ae257d36eb7","applyUrl":"https://jobs.ashbyhq.com/fireworks/a2850702-dea3-4e2c-a3ec-7ae257d36eb7/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
As a Training Infrastructure Engineer, you'll design, build, and optimize the infrastructure that powers our large-scale model training operations. Your work will be essential to developing high-performance AI training infrastructure. You'll collaborate with AI researchers and engineers to create robust training pipelines, optimize distributed training workloads, and ensure reliable model development.
Design and implement scalable infrastructure for large-scale model training workloads
Develop and maintain distributed training pipelines for LLMs and multimodal models
Optimize training performance across multiple GPUs, nodes, and data centers
Implement monitoring, logging, and debugging tools for training operations
Architect and maintain data storage solutions for large-scale training datasets
Automate infrastructure provisioning, scaling, and orchestration for model training
Collaborate with researchers to implement and optimize training methodologies
Analyze and improve efficiency, scalability, and cost-effectiveness of training systems
Troubleshoot complex performance issues in distributed training environments
Bachelor's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience
3+ years of experience with distributed systems and ML infrastructure
Experience with PyTorch
Proficiency in cloud platforms (AWS, GCP, Azure)
Experience with containerization, orchestration (Kubernetes, Docker)
Knowledge of distributed training techniques (data parallelism, model parallelism, FSDP)
Master's or PhD in Computer Science or related field
Experience training large language models or multimodal AI systems
Experience with ML workflow orchestration tools
Background in optimizing high-performance distributed computing systems
Familiarity with ML DevOps practices
Contributions to open-source ML infrastructure or related projects
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE: \n\nAs a Training Infrastructure Engineer, you'll design, build, and optimize the infrastructure that powers our large-scale model training operations. Your work will be essential to developing high-performance AI training infrastructure. You'll collaborate with AI researchers and engineers to create robust training pipelines, optimize distributed training workloads, and ensure reliable model development.\n\n\nKEY RESPONSIBILITIES:\n\n - Design and implement scalable infrastructure for large-scale model training workloads\n\n - Develop and maintain distributed training pipelines for LLMs and multimodal models\n\n - Optimize training performance across multiple GPUs, nodes, and data centers\n\n - Implement monitoring, logging, and debugging tools for training operations\n\n - Architect and maintain data storage solutions for large-scale training datasets\n\n - Automate infrastructure provisioning, scaling, and orchestration for model training\n\n - Collaborate with researchers to implement and optimize training methodologies\n\n - Analyze and improve efficiency, scalability, and cost-effectiveness of training systems\n\n - Troubleshoot complex performance issues in distributed training environments\n\n\nMINIMUM QUALIFICATIONS:\n\n - Bachelor's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience\n\n - 3+ years of experience with distributed systems and ML infrastructure\n\n - Experience with PyTorch\n\n - Proficiency in cloud platforms (AWS, GCP, Azure)\n\n - Experience with containerization, orchestration (Kubernetes, Docker)\n\n - Knowledge of distributed training techniques (data parallelism, model parallelism, FSDP)\n\n\nPREFERRED QUALIFICATIONS:\n\n - Master's or PhD in Computer Science or related field\n\n - Experience training large language models or multimodal AI systems\n\n - Experience with ML workflow orchestration tools\n\n - Background in optimizing high-performance distributed computing systems\n\n - Familiarity with ML DevOps practices\n\n - Contributions to open-source ML infrastructure or related projects\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"7ad6d17e-950e-4413-be33-9c1489f069d8","title":"Member of Technical Staff, Performance Optimization","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2025-05-06T20:04:42.424+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/7ad6d17e-950e-4413-be33-9c1489f069d8","applyUrl":"https://jobs.ashbyhq.com/fireworks/7ad6d17e-950e-4413-be33-9c1489f069d8/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We're looking for a Software Engineer focused on Performance Optimization to help push the boundaries of speed and efficiency across our AI infrastructure. In this role, you'll take ownership of optimizing performance at every layer of the stack—from low-level GPU kernels to large-scale distributed systems. A key focus will be maximizing the performance of our most demanding workloads, including large language models (LLMs), vision-language models (VLMs), and next-generation video models.
You’ll work closely with teams across research, infrastructure, and systems to identify performance bottlenecks, implement cutting-edge optimizations, and scale our AI systems to meet the demands of real-world production use cases. Your work will directly impact the speed, scalability, and cost-effectiveness of some of the most advanced generative AI models in the world.
Optimize system and GPU performance for high-throughput AI workloads across training and inference
Analyze and improve latency, throughput, memory usage, and compute efficiency
Profile system performance to detect and resolve GPU- and kernel-level bottlenecks
Implement low-level optimizations using CUDA, Triton, and other performance tooling
Drive improvements in execution speed and resource utilization for large-scale model workloads (LLMs, VLMs, and video models)
Collaborate with ML researchers to co-design and tune model architectures for hardware efficiency
Improve support for mixed precision, quantization, and model graph optimization
Build and maintain performance benchmarking and monitoring infrastructure
Scale inference and training systems across multi-GPU, multi-node environments
Evaluate and integrate optimizations for emerging hardware accelerators and specialized runtimes
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience
5+ years of experience working on performance optimization or high-performance computing systems
Proficiency in CUDA or ROCm and experience with GPU profiling tools (e.g., Nsight, nvprof, CUPTI)
Familiarity with PyTorch and performance-critical model execution
Experience with distributed system debugging and optimization in multi-GPU environments
Deep understanding of GPU architecture, parallel programming models, and compute kernels
Master’s or PhD in Computer Science, Electrical Engineering, or a related field
Experience optimizing large models for training and inference (LLMs, VLMs, or video models)
Knowledge of compiler stacks or ML compilers (e.g., torch.compile, Triton, XLA)
Contributions to open-source ML or HPC infrastructure
Familiarity with cloud-scale AI infrastructure and orchestration tools (e.g., Kubernetes)
Background in ML systems engineering or hardware-aware model design
Implement fully asynchronous low-latency sampling for large language models integrated with structured outputs
Implement GPU kernels for the new low-precision scheme and run experiments to find optimal speed-quality tradeoff
Build a distributed router with a custom load-balancing algorithm to optimize LLM cache efficiency
Define metrics and build harness for finding optimal performance configuration (e.g. sharding, precision) for a given class of model
Determine and implement in PyTorch an optimal sharding scheme for a novel attention variant
Optimize communication patterns in RDMA networks (Infiniband, RoCE)
Debug numerical instabilities for a given model for a small portion of requests when deployed at scale
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE: \n\nWe're looking for a Software Engineer focused on Performance Optimization to help push the boundaries of speed and efficiency across our AI infrastructure. In this role, you'll take ownership of optimizing performance at every layer of the stack—from low-level GPU kernels to large-scale distributed systems. A key focus will be maximizing the performance of our most demanding workloads, including large language models (LLMs), vision-language models (VLMs), and next-generation video models.\n\nYou’ll work closely with teams across research, infrastructure, and systems to identify performance bottlenecks, implement cutting-edge optimizations, and scale our AI systems to meet the demands of real-world production use cases. Your work will directly impact the speed, scalability, and cost-effectiveness of some of the most advanced generative AI models in the world.\n\n\nKEY RESPONSIBILITIES:\n\n - Optimize system and GPU performance for high-throughput AI workloads across training and inference\n\n - Analyze and improve latency, throughput, memory usage, and compute efficiency\n\n - Profile system performance to detect and resolve GPU- and kernel-level bottlenecks\n\n - Implement low-level optimizations using CUDA, Triton, and other performance tooling\n\n - Drive improvements in execution speed and resource utilization for large-scale model workloads (LLMs, VLMs, and video models)\n\n - Collaborate with ML researchers to co-design and tune model architectures for hardware efficiency\n\n - Improve support for mixed precision, quantization, and model graph optimization\n\n - Build and maintain performance benchmarking and monitoring infrastructure\n\n - Scale inference and training systems across multi-GPU, multi-node environments\n\n - Evaluate and integrate optimizations for emerging hardware accelerators and specialized runtimes\n\n\nMINIMUM QUALIFICATIONS:\n\n - Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience\n\n - 5+ years of experience working on performance optimization or high-performance computing systems\n\n - Proficiency in CUDA or ROCm and experience with GPU profiling tools (e.g., Nsight, nvprof, CUPTI)\n\n - Familiarity with PyTorch and performance-critical model execution\n\n - Experience with distributed system debugging and optimization in multi-GPU environments\n\n - Deep understanding of GPU architecture, parallel programming models, and compute kernels\n\n\nPREFERRED QUALIFICATIONS:\n\n - Master’s or PhD in Computer Science, Electrical Engineering, or a related field\n\n - Experience optimizing large models for training and inference (LLMs, VLMs, or video models)\n\n - Knowledge of compiler stacks or ML compilers (e.g., torch.compile, Triton, XLA)\n\n - Contributions to open-source ML or HPC infrastructure\n\n - Familiarity with cloud-scale AI infrastructure and orchestration tools (e.g., Kubernetes)\n\n - Background in ML systems engineering or hardware-aware model design\n\n\nEXAMPLE PROJECTS:\n\n - Implement fully asynchronous low-latency sampling for large language models integrated with structured outputs\n\n - Implement GPU kernels for the new low-precision scheme and run experiments to find optimal speed-quality tradeoff\n\n - Build a distributed router with a custom load-balancing algorithm to optimize LLM cache efficiency\n\n - Define metrics and build harness for finding optimal performance configuration (e.g. sharding, precision) for a given class of model\n\n - Determine and implement in PyTorch an optimal sharding scheme for a novel attention variant\n\n - Optimize communication patterns in RDMA networks (Infiniband, RoCE)\n\n - Debug numerical instabilities for a given model for a small portion of requests when deployed at scale\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"fc3845e6-e8ba-4756-a03e-654f14ce605b","title":"Applied Machine Learning Engineer","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2025-05-09T20:15:59.468+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/fc3845e6-e8ba-4756-a03e-654f14ce605b","applyUrl":"https://jobs.ashbyhq.com/fireworks/fc3845e6-e8ba-4756-a03e-654f14ce605b/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.
Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.
Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.
Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.
New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.
Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.
Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.
Bachelor’s degree in Computer Science, Engineering, or a related technical field.
5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.
Robust coding skills required, preferably with proficiency in Python.
Demonstrated ability to lead and execute complex technical projects with a focus on customer success.
Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.
Master’s degree in Computer Science, Engineering, or a related technical field.
Experience working in a startup or fast-paced environment.
Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).
Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nAs an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.\n\n\n\n\nKEY RESPONSIBILITIES:\n\n - Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.\n\n - Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.\n\n - Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.\n\n - Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.\n\n - New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.\n\n - Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.\n\n - Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.\n\n\nMINIMUM QUALIFICATIONS:\n\n - Bachelor’s degree in Computer Science, Engineering, or a related technical field.\n\n - 5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.\n\n - Robust coding skills required, preferably with proficiency in Python.\n\n - Demonstrated ability to lead and execute complex technical projects with a focus on customer success.\n\n - Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.\n\n\nPREFERRED QUALIFICATIONS:\n\n - Master’s degree in Computer Science, Engineering, or a related technical field.\n\n - Experience working in a startup or fast-paced environment.\n\n - Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).\n\n - Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"a8abf746-17f5-45e3-a72e-085ccb8f2d74","title":"Member of Technical Staff, Cloud Infrastructure","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2025-06-20T19:29:20.147+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/a8abf746-17f5-45e3-a72e-085ccb8f2d74","applyUrl":"https://jobs.ashbyhq.com/fireworks/a8abf746-17f5-45e3-a72e-085ccb8f2d74/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
As a Software Engineer on our Cloud Infrastructure team, you'll be at the forefront, architecting and building the foundational systems that power Fireworks AI's revolutionary generative AI platform. You'll spearhead the creation of one of the world's first virtual clouds, seamlessly serving AI workloads across the globe and every cloud provider. Your mission: to deliver unparalleled reliability, efficiency, and scalability, fueling the world's most innovative AI products.This is a highly technical role requiring deep expertise in distributed systems, cloud-native infrastructure, and machine learning platforms. You’ll partner closely with engineering partners, product teams, and infrastructure stakeholders to design solutions that balance performance, cost-efficiency, and operational simplicity across compute, storage, and networking layers.
Architect and build scalable, resilient, and high-performance backend infrastructure to support distributed training, inference, and data processing pipelines.
Lead technical design discussions, mentor other engineers, and establish best practices for building and operating large-scale ML infrastructure.
Design and implement core backend services (e.g., job schedulers, resource managers, autoscalers, model serving layers) with a focus on efficiency and low latency.
Drive infrastructure optimization initiatives, including compute cost reduction, storage lifecycle management, and network performance tuning.
Collaborate cross-functionally with ML, DevOps, and product teams to translate research and product needs into robust infrastructure solutions.
Continuously evaluate and integrate cloud-native and open-source technologies (e.g., Kubernetes, Kubeflow, MLFlow) to enhance our platform’s capabilities and reliability.
Own end-to-end systems from design to deployment and observability, with a strong emphasis on reliability, fault tolerance, and operational excellence.
Ensuring System Reliability: Ensure systems are designed and implemented with high availability, scalability, and performance. Focus on fault tolerance, disaster recovery, identifying and removing scaling bottlenecks, and performance optimization across our multi-cloud infrastructure.
Observability & Monitoring: Develop, implement, and maintain comprehensive monitoring, alerting, logging, and tracing solutions to provide deep insights into system health and performance
Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
5+ years of experience designing and building backend infrastructure in cloud environments (e.g., AWS, GCP, Azure).
Proven experience in ML infrastructure and tooling (e.g., PyTorch, TensorFlow, Vertex AI, SageMaker, Kubernetes, etc.).
Strong software development skills in languages like Python, or C++.
Deep understanding of distributed systems fundamentals: scheduling, orchestration, storage, networking, and compute optimization.
Master’s or PhD in Computer Science or related field.
Experience leading infrastructure projects supporting large-scale ML/AI workloads or high-throughput systems.
Familiarity with infrastructure-as-code and CI/CD tooling (e.g., Terraform, ArgoCD, GitOps).
Track record of driving system performance, reliability, and cost-efficiency improvements.
Contributions to open-source cloud or ML infrastructure projects a plus.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nAs a Software Engineer on our Cloud Infrastructure team, you'll be at the forefront, architecting and building the foundational systems that power Fireworks AI's revolutionary generative AI platform. You'll spearhead the creation of one of the world's first virtual clouds, seamlessly serving AI workloads across the globe and every cloud provider. Your mission: to deliver unparalleled reliability, efficiency, and scalability, fueling the world's most innovative AI products.This is a highly technical role requiring deep expertise in distributed systems, cloud-native infrastructure, and machine learning platforms. You’ll partner closely with engineering partners, product teams, and infrastructure stakeholders to design solutions that balance performance, cost-efficiency, and operational simplicity across compute, storage, and networking layers.\n\n\nKEY RESPONSIBILITIES:\n\n - Architect and build scalable, resilient, and high-performance backend infrastructure to support distributed training, inference, and data processing pipelines.\n\n - Lead technical design discussions, mentor other engineers, and establish best practices for building and operating large-scale ML infrastructure.\n\n - Design and implement core backend services (e.g., job schedulers, resource managers, autoscalers, model serving layers) with a focus on efficiency and low latency.\n\n - Drive infrastructure optimization initiatives, including compute cost reduction, storage lifecycle management, and network performance tuning.\n\n - Collaborate cross-functionally with ML, DevOps, and product teams to translate research and product needs into robust infrastructure solutions.\n\n - Continuously evaluate and integrate cloud-native and open-source technologies (e.g., Kubernetes, Kubeflow, MLFlow) to enhance our platform’s capabilities and reliability.\n\n - Own end-to-end systems from design to deployment and observability, with a strong emphasis on reliability, fault tolerance, and operational excellence.\n\n - Ensuring System Reliability: Ensure systems are designed and implemented with high availability, scalability, and performance. Focus on fault tolerance, disaster recovery, identifying and removing scaling bottlenecks, and performance optimization across our multi-cloud infrastructure.\n\n - Observability & Monitoring: Develop, implement, and maintain comprehensive monitoring, alerting, logging, and tracing solutions to provide deep insights into system health and performance \n\n\nMINIMUM QUALIFICATIONS:\n\n - Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).\n\n - 5+ years of experience designing and building backend infrastructure in cloud environments (e.g., AWS, GCP, Azure).\n\n - Proven experience in ML infrastructure and tooling (e.g., PyTorch, TensorFlow, Vertex AI, SageMaker, Kubernetes, etc.).\n\n - Strong software development skills in languages like Python, or C++.\n\n - Deep understanding of distributed systems fundamentals: scheduling, orchestration, storage, networking, and compute optimization.\n\n\nPREFERRED QUALIFICATIONS:\n\n - Master’s or PhD in Computer Science or related field.\n\n - Experience leading infrastructure projects supporting large-scale ML/AI workloads or high-throughput systems.\n\n - Familiarity with infrastructure-as-code and CI/CD tooling (e.g., Terraform, ArgoCD, GitOps).\n\n - Track record of driving system performance, reliability, and cost-efficiency improvements.\n\n - Contributions to open-source cloud or ML infrastructure projects a plus.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"c5b1678b-29ba-4e12-8033-29fbdf34b92a","title":"Forward Deployed Product Manager","department":"Product","team":"Product","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2025-07-15T03:36:13.638+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/c5b1678b-29ba-4e12-8033-29fbdf34b92a","applyUrl":"https://jobs.ashbyhq.com/fireworks/c5b1678b-29ba-4e12-8033-29fbdf34b92a/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
The ideal Forward Deployed Product Manager (FDPM) candidate is a customer obsessed AI product manager who thrives on our customers’ successful outcomes. You will spend most of your time talking to customers and connecting their technical requirements to the Fireworks product offerings. FDPMs ensure our customers’ success by building and delivering solutions that meet their needs. They translate customer feedback into internal product requirements for scalable products that land with customers.
Engage directly with customers from fast-moving startups to large enterprises, to identify use cases and convert interest into long-term usage and expansion
Define and propose tailored solutions and proof-of-concepts (POCs) that demonstrate the value of Fireworks’ platform in real customer environments.
Lead onboarding and implementation efforts, including fine-tuning workflows, latency benchmarks, API integration, and infrastructure alignment.
Act as a trusted technical advisor to customers, helping shape their GenAI strategy using Fireworks infrastructure.
Translate customer insights into structured product definition, identifying common themes and high-leverage feature requests.
Collaborate closely with engineering and applied ML teams to align customer needs with technical roadmap
Drive execution of product development, ensuring that new products land successfully with customers
Oversee Fireworks roadmap, ensuring that reflects customer needs
Strong technical background (CS/EECE background and/or production level development experience) or technical product management experience
Intimate familiarity with LLMs, fine-tuning, model inference, agents etc.
2 - 5+ years of experience in products for software engineers (hiring at multiple levels for this role)
Strong customer interaction skills, deep customer success focus
Ability to communicate highly technical concepts to all kinds of audiences including the latest AI developments
Focus on driving outcomes, not just technical milestones
Ability to navigate complex customer/technical scenarios and come up with creative solutions
Prior experience in technical product management roles with high degree of customer interactions
Interest in generative AI or developer tools
Early startup or founding experience
Prior technical leadership / technical PM experience
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nThe ideal Forward Deployed Product Manager (FDPM) candidate is a customer obsessed AI product manager who thrives on our customers’ successful outcomes. You will spend most of your time talking to customers and connecting their technical requirements to the Fireworks product offerings. FDPMs ensure our customers’ success by building and delivering solutions that meet their needs. They translate customer feedback into internal product requirements for scalable products that land with customers. \n\n\nKEY RESPONSIBILITIES:\n\n\nCUSTOMER JOURNEY\n\n - Engage directly with customers from fast-moving startups to large enterprises, to identify use cases and convert interest into long-term usage and expansion \n\n - Define and propose tailored solutions and proof-of-concepts (POCs) that demonstrate the value of Fireworks’ platform in real customer environments.\n\n - Lead onboarding and implementation efforts, including fine-tuning workflows, latency benchmarks, API integration, and infrastructure alignment.\n\n - Act as a trusted technical advisor to customers, helping shape their GenAI strategy using Fireworks infrastructure.\n\n\nFIREWORKS PRODUCT ROADMAP\n\n - Translate customer insights into structured product definition, identifying common themes and high-leverage feature requests.\n\n - Collaborate closely with engineering and applied ML teams to align customer needs with technical roadmap\n\n - Drive execution of product development, ensuring that new products land successfully with customers\n\n - Oversee Fireworks roadmap, ensuring that reflects customer needs\n\n\nMINIMUM REQUIREMENTS:\n\n - Strong technical background (CS/EECE background and/or production level development experience) or technical product management experience\n\n - Intimate familiarity with LLMs, fine-tuning, model inference, agents etc.\n\n - 2 - 5+ years of experience in products for software engineers (hiring at multiple levels for this role)\n\n - Strong customer interaction skills, deep customer success focus\n\n - Ability to communicate highly technical concepts to all kinds of audiences including the latest AI developments\n\n - Focus on driving outcomes, not just technical milestones\n\n - Ability to navigate complex customer/technical scenarios and come up with creative solutions\n\n\nPREFERRED QUALIFICATIONS:\n\n - Prior experience in technical product management roles with high degree of customer interactions\n\n - Interest in generative AI or developer tools\n\n - Early startup or founding experience\n\n - Prior technical leadership / technical PM experience\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"cca38fd5-9cbd-4cee-8fdb-d6e6d230b036","title":"Member of Technical Staff, Evals & Post-Training Product","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2025-10-30T22:54:05.957+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/cca38fd5-9cbd-4cee-8fdb-d6e6d230b036","applyUrl":"https://jobs.ashbyhq.com/fireworks/cca38fd5-9cbd-4cee-8fdb-d6e6d230b036/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We are seeking a Member of Technical Staff, Evals & Post-Training Product to help define how developers improve models on Fireworks. This role sits at the intersection of product engineering, developer experience, and model quality.
You will build the products and workflows that connect evaluation and post-training into a continuous loop: helping internal teams run evals at scale, enabling external developers through our open-source Eval Protocol SDK, and owning key product experiences for fine-tuning custom models on Fireworks.
You will work across the stack—from APIs, SDKs, and backend systems to user-facing product surfaces in the web app—to make it easier for users to author evals, understand results, fine-tune models, and iterate quickly. You will also work directly with customers and internal teams to identify friction, support real-world use cases, and turn repeated pain points into reusable product capabilities.
Build internal eval workflows: Design and scale evaluation tooling used by internal teams to measure model quality, compare model changes, and inform post-training decisions.
Own fine-tuning product experiences: Build and improve user-facing product workflows for post-training, including fine-tuning experiences across SFT, RFT, and related model-improvement capabilities.
Work closely with users: Partner with customers and internal stakeholders to understand evaluation and fine-tuning needs, support high-priority engagements, triage issues, and convert bespoke workflows into productized solutions.
1 - 7 years of software engineering experience (We are hiring at multiple levels for this role).
Hands-on experience with LLM evaluations and/or post-training methods: How to design useful evals and use their results to guide model improvement.
Product Engineering Skills: The ability to work across backend systems and developer-facing product surfaces. Comfortable shipping full-stack features when needed.
Understanding of the GenAI Lifecycle: You understand the end-to-end workflow—from prompting a base model to curating a dataset, fine-tuning, and productionizing agents—and how these steps interconnect.
User-Centric Mindset: Willing to talk to users, triage GitHub issues for open-source projects, and build products from scratch to serve emerging needs.
3+ years of software engineering experience.
Domain-Specific Evaluation Experience: Strong familiarity with designing and running evaluations for domain-specific use cases (e.g. medical, legal, coding, or custom internal datasets).
Open Source Contributions: Prior contributions to developer tools or AI/ML repositories.
Inference & Hardware Knowledge: Interest in the hardware side of AI—understanding GPU constraints, inference optimization techniques, and how they relate to model performance.
Startup DNA: Experience in fast-paced environments where you own features end-to-end.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nWe are seeking a Member of Technical Staff, Evals & Post-Training Product to help define how developers improve models on Fireworks. This role sits at the intersection of product engineering, developer experience, and model quality.\n\nYou will build the products and workflows that connect evaluation and post-training into a continuous loop: helping internal teams run evals at scale, enabling external developers through our open-source Eval Protocol SDK, and owning key product experiences for fine-tuning custom models on Fireworks.\n\nYou will work across the stack—from APIs, SDKs, and backend systems to user-facing product surfaces in the web app—to make it easier for users to author evals, understand results, fine-tune models, and iterate quickly. You will also work directly with customers and internal teams to identify friction, support real-world use cases, and turn repeated pain points into reusable product capabilities.\n\n\nKEY RESPONSIBILITIES:\n\n - Build internal eval workflows: Design and scale evaluation tooling used by internal teams to measure model quality, compare model changes, and inform post-training decisions.\n\n - Own fine-tuning product experiences: Build and improve user-facing product workflows for post-training, including fine-tuning experiences across SFT, RFT, and related model-improvement capabilities.\n\n - Work closely with users: Partner with customers and internal stakeholders to understand evaluation and fine-tuning needs, support high-priority engagements, triage issues, and convert bespoke workflows into productized solutions.\n\n\nMINIMUM REQUIREMENTS:\n\n - 1 - 7 years of software engineering experience (We are hiring at multiple levels for this role).\n\n - Hands-on experience with LLM evaluations and/or post-training methods: How to design useful evals and use their results to guide model improvement.\n\n - Product Engineering Skills: The ability to work across backend systems and developer-facing product surfaces. Comfortable shipping full-stack features when needed.\n\n - Understanding of the GenAI Lifecycle: You understand the end-to-end workflow—from prompting a base model to curating a dataset, fine-tuning, and productionizing agents—and how these steps interconnect.\n\n - User-Centric Mindset: Willing to talk to users, triage GitHub issues for open-source projects, and build products from scratch to serve emerging needs.\n\n\nPREFERRED QUALIFICATIONS:\n\n - 3+ years of software engineering experience.\n\n - Domain-Specific Evaluation Experience: Strong familiarity with designing and running evaluations for domain-specific use cases (e.g. medical, legal, coding, or custom internal datasets).\n\n - Open Source Contributions: Prior contributions to developer tools or AI/ML repositories.\n\n - Inference & Hardware Knowledge: Interest in the hardware side of AI—understanding GPU constraints, inference optimization techniques, and how they relate to model performance.\n\n - Startup DNA: Experience in fast-paced environments where you own features end-to-end.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"82013447-2713-46ca-aab1-b0a34f7b565a","title":" Software Engineer, LLM Infrastructure","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2025-11-05T16:54:08.032+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/82013447-2713-46ca-aab1-b0a34f7b565a","applyUrl":"https://jobs.ashbyhq.com/fireworks/82013447-2713-46ca-aab1-b0a34f7b565a/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
As a Software Engineer on our AI Infrastructure team, you will help design the core systems that power Fireworks AI’s generative AI platform. You will help build infrastructure and tools that ensure the reliability, performance, quality, and availability of our AI system.
Our mission is to make Fireworks AI the most reliable and user friendly generative AI platform in the world. You will partner closely with our cloud infrastructure team, product team, and performance team to deliver infrastructure that bridges the gap between our customer and the ultra-performant proprietary Fireworks inference engine.
Contribute to the design and development of scalable backend infrastructure that supports distributed training, inference, and data pipelines
Build and maintain core backend services such as LLM CI/CD pipeline, control plane, and model serving systems
Support performance optimization, cost efficiency, and reliability improvements across compute, storage, and networking layers
Building frameworks and safeguards to ensure Fireworks AI has the best model quality in the industry
Collaborate with performance, training, and product teams to translate research and product needs into infrastructure solutions
Participate in code reviews, technical discussions, and continuous integration and deployment processes
Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
3 years of experience in software engineering, with a focus on infrastructure or machine learning systems
Strong programming skills in Python, Go, or a similar language
Proven experience in ML infrastructure and tooling (e.g., PyTorch, MLflow, Vertex AI, SageMaker, Kubernetes, etc.).
Basic understanding of LLM knowledge (e.g., context length, disaggregated prefill, KV cache memory estimation, etc)
5+ years of experience in software engineering, with a focus on infrastructure or machine learning systems
Experience with open source inference engine like vLLM, Sglang, or TRT-LLM
Contributions to open-source infrastructure or ML projects
Experience in building large scale ML/MLOps infrastructure
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nAs a Software Engineer on our AI Infrastructure team, you will help design the core systems that power Fireworks AI’s generative AI platform. You will help build infrastructure and tools that ensure the reliability, performance, quality, and availability of our AI system. \n\nOur mission is to make Fireworks AI the most reliable and user friendly generative AI platform in the world. You will partner closely with our cloud infrastructure team, product team, and performance team to deliver infrastructure that bridges the gap between our customer and the ultra-performant proprietary Fireworks inference engine. \n\n\nKEY RESPONSIBILITIES:\n\n - Contribute to the design and development of scalable backend infrastructure that supports distributed training, inference, and data pipelines\n\n - Build and maintain core backend services such as LLM CI/CD pipeline, control plane, and model serving systems\n\n - Support performance optimization, cost efficiency, and reliability improvements across compute, storage, and networking layers\n\n - Building frameworks and safeguards to ensure Fireworks AI has the best model quality in the industry\n\n - Collaborate with performance, training, and product teams to translate research and product needs into infrastructure solutions\n\n - Participate in code reviews, technical discussions, and continuous integration and deployment processes\n\n\nMINIMUM QUALIFICATIONS:\n\n - Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)\n\n - 3 years of experience in software engineering, with a focus on infrastructure or machine learning systems\n\n - Strong programming skills in Python, Go, or a similar language\n\n - Proven experience in ML infrastructure and tooling (e.g., PyTorch, MLflow, Vertex AI, SageMaker, Kubernetes, etc.).\n\n - Basic understanding of LLM knowledge (e.g., context length, disaggregated prefill, KV cache memory estimation, etc) \n\n\nPREFERRED QUALIFICATIONS:\n\n - 5+ years of experience in software engineering, with a focus on infrastructure or machine learning systems\n\n - Experience with open source inference engine like vLLM, Sglang, or TRT-LLM\n\n - Contributions to open-source infrastructure or ML projects\n\n - Experience in building large scale ML/MLOps infrastructure\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"976cf215-3710-4136-aac8-f0c0f08ef45e","title":"Security Engineer","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-01-20T19:32:33.123+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/976cf215-3710-4136-aac8-f0c0f08ef45e","applyUrl":"https://jobs.ashbyhq.com/fireworks/976cf215-3710-4136-aac8-f0c0f08ef45e/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
Security is the foundation of trust in AI systems. As the Security Engineer at Fireworks AI, you will play a key role in designing, implementing and operating security controls across AI infrastructure, AI platforms and internal systems. You will work closely with the multiple teams to strengthen our security posture and support our rapid growth. As more organizations rely on large language models and cloud-native AI services, ensuring the confidentiality, integrity, and availability of data, models, and infrastructure is paramount. This role plays a critical part in building that trust by designing and embedding security across layers of our technology stack.
Design and build security-focused software and platform capabilities to protect customer data, models, and services across our multi-cloud infrastructure, including encryption, identity and access management, secure API gateways, secure model execution, and sandboxing strategies.
Perform security reviews of cloud-native architectures—including Kubernetes clusters, multi-cloud workloads, and distributed data stores—and build integrated systems for continuous security monitoring, anomaly detection, and automated response.
Embed security into CI/CD pipelines using a DevSecOps approach, implementing automated scanning, policy enforcement, and secure-by-default build and deployment workflows.
Apply a build-over-buy philosophy by designing and developing in-house security tooling and automation where it provides better control, scalability, and integration than off-the-shelf solutions.
Build and operate a comprehensive vulnerability management program, partnering with various teams to remediate risks across applications, containers, cloud infrastructure, and dependencies.
Operate and continuously improve security operations, including detection engineering, alert triage, incident response, and continuous improvement through post-incident reviews.
Participate in red/blue team exercises, tabletop simulations, and post-incident root cause analysis to strengthen security resilience.
Embed compliance and regulatory controls into infrastructure and product layers (e.g., SOC 2, ISO 27001, ISO42001, HIPAA, PCI-DSS, GDPR).
3 to 7 years of experience in software engineering or security engineering with a strong focus on security, infrastructure, or cloud-native systems.
Proficient in Python and/or Go with experience in designing production-grade systems.
Strong understanding of cloud-native architectures using GCP, particularly in the area of network segregation, authentication, authorization, encryption, data protection, intrusion detection, and cloud-specific security benchmarks.
Hands-on experience with Kubernetes, Docker, and containerized production environments; deep knowledge of Kubernetes internals and native security controls is a strong plus.
Familiarity with security tooling in managed CI/CD environments (e.g., GitHub Actions, Harness, CircleCI).
Solid experience working in Linux environments, including system administration, debugging, and automation via command-line tooling.
Familiarity with modern identity and access controls (SAML, OAuth, OIDC, SSO, RBAC/ABAC).
Experience designing secure multi-cloud deployments and zero-trust architectures.
Experience designing, operating, and securing large-scale Kubernetes platforms, including control plane security, node hardening, and multi-tenant isolation.
Experience designing, operating, and securing large-scale multi-cloud platforms across AWS, GCP, Azure, Oracle Cloud, and GPU as service cloud providers.
Proficiency with infrastructure-as-code using Terraform and Python, including experience building modular policy-as-code frameworks.
Strong understanding of data protection techniques, including encryption at rest/in transit, tokenization, key management, and confidential computing.
Experience integrating security into microservice architectures, service meshes, and distributed systems.
Hands-on experience securing LLM/ML platforms, model inference infrastructure, GPU clusters, or data labeling pipelines.
Experience designing detection engineering pipelines across cloud audit logs, network telemetry, and application signals.
Experience building large-scale IAM and PAM platforms using least-privilege, workload identity, and just-in-time access.
Familiarity with container image vulnerability remediation, security, SBOM generation, and software supply chain security.
Experience building, implementing and operating security automation platforms for incident response and security operations.
Familiarity with compliance tooling and frameworks (e.g., Vanta, SOC 2, ISO 27001, ISO 42001, PCI-DSS).
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nSecurity is the foundation of trust in AI systems. As the Security Engineer at Fireworks AI, you will play a key role in designing, implementing and operating security controls across AI infrastructure, AI platforms and internal systems. You will work closely with the multiple teams to strengthen our security posture and support our rapid growth. As more organizations rely on large language models and cloud-native AI services, ensuring the confidentiality, integrity, and availability of data, models, and infrastructure is paramount. This role plays a critical part in building that trust by designing and embedding security across layers of our technology stack.\n\n\nKEY RESPONSIBILITIES:\n\n - Design and build security-focused software and platform capabilities to protect customer data, models, and services across our multi-cloud infrastructure, including encryption, identity and access management, secure API gateways, secure model execution, and sandboxing strategies.\n\n - Perform security reviews of cloud-native architectures—including Kubernetes clusters, multi-cloud workloads, and distributed data stores—and build integrated systems for continuous security monitoring, anomaly detection, and automated response.\n\n - Embed security into CI/CD pipelines using a DevSecOps approach, implementing automated scanning, policy enforcement, and secure-by-default build and deployment workflows.\n\n - Apply a build-over-buy philosophy by designing and developing in-house security tooling and automation where it provides better control, scalability, and integration than off-the-shelf solutions.\n\n - Build and operate a comprehensive vulnerability management program, partnering with various teams to remediate risks across applications, containers, cloud infrastructure, and dependencies.\n\n - Operate and continuously improve security operations, including detection engineering, alert triage, incident response, and continuous improvement through post-incident reviews.\n\n - Participate in red/blue team exercises, tabletop simulations, and post-incident root cause analysis to strengthen security resilience.\n\n - Embed compliance and regulatory controls into infrastructure and product layers (e.g., SOC 2, ISO 27001, ISO42001, HIPAA, PCI-DSS, GDPR).\n \n \n\n\nMINIMUM QUALIFICATIONS:\n\n - 3 to 7 years of experience in software engineering or security engineering with a strong focus on security, infrastructure, or cloud-native systems. \n\n - Proficient in Python and/or Go with experience in designing production-grade systems.\n\n - Strong understanding of cloud-native architectures using GCP, particularly in the area of network segregation, authentication, authorization, encryption, data protection, intrusion detection, and cloud-specific security benchmarks.\n\n - Hands-on experience with Kubernetes, Docker, and containerized production environments; deep knowledge of Kubernetes internals and native security controls is a strong plus.\n\n - Familiarity with security tooling in managed CI/CD environments (e.g., GitHub Actions, Harness, CircleCI).\n\n - Solid experience working in Linux environments, including system administration, debugging, and automation via command-line tooling.\n\n - Familiarity with modern identity and access controls (SAML, OAuth, OIDC, SSO, RBAC/ABAC).\n\n\nPREFERRED QUALIFICATIONS:\n\n - Experience designing secure multi-cloud deployments and zero-trust architectures.\n\n - Experience designing, operating, and securing large-scale Kubernetes platforms, including control plane security, node hardening, and multi-tenant isolation.\n\n - Experience designing, operating, and securing large-scale multi-cloud platforms across AWS, GCP, Azure, Oracle Cloud, and GPU as service cloud providers.\n\n - Proficiency with infrastructure-as-code using Terraform and Python, including experience building modular policy-as-code frameworks.\n\n - Strong understanding of data protection techniques, including encryption at rest/in transit, tokenization, key management, and confidential computing.\n\n - Experience integrating security into microservice architectures, service meshes, and distributed systems.\n\n - Hands-on experience securing LLM/ML platforms, model inference infrastructure, GPU clusters, or data labeling pipelines.\n\n - Experience designing detection engineering pipelines across cloud audit logs, network telemetry, and application signals.\n\n - Experience building large-scale IAM and PAM platforms using least-privilege, workload identity, and just-in-time access.\n\n - Familiarity with container image vulnerability remediation, security, SBOM generation, and software supply chain security.\n\n - Experience building, implementing and operating security automation platforms for incident response and security operations.\n\n - Familiarity with compliance tooling and frameworks (e.g., Vanta, SOC 2, ISO 27001, ISO 42001, PCI-DSS).\n \n \n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"492db6a8-c757-4c4e-a2b3-f2ed183f8e6f","title":"Member of Technical Staff, Software Engineer","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-03-08T23:23:18.627+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/492db6a8-c757-4c4e-a2b3-f2ed183f8e6f","applyUrl":"https://jobs.ashbyhq.com/fireworks/492db6a8-c757-4c4e-a2b3-f2ed183f8e6f/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
You’ll be a core builder of the backend systems that power Fireworks:
Our main web application
Model and fine-tuning job orchestration
Billing and enterprise features
Accounts, org management, access controls
Policy enforcement and governance
APIs and developer tooling
And many other cool things!
This is platform engineering with product impact. Your systems will directly shape how customers build on top of AI. You’ll work closely with product, frontend, infra, and GTM to ship end-to-end features — not just tickets.
Design and build scalable backend services
Own major product surfaces from architecture to production
Improve reliability, performance, and developer experience
Work directly with customers to understand pain points
Ship enterprise-grade features without enterprise slowness
Use AI tooling aggressively — we expect you to automate yourself
You like building real products, not just infrastructure for infrastructure’s sake
You enjoy driving initiatives across teams to get things done
You think in terms of systems, tradeoffs, and business impact
You care about developer experience and clean abstractions
You’re curious about AI and want to build where the future is going
You want ownership, not task lists
Comfortable collaborating with both humans and AI systems (Yes, We’re Serious)
5+ years of experience helping humans solve real problems
2+ years of working with AI — agents, bots, chats, or building on top of models
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nYou’ll be a core builder of the backend systems that power Fireworks:\n\n - Our main web application\n\n - Model and fine-tuning job orchestration\n\n - Billing and enterprise features\n\n - Accounts, org management, access controls\n\n - Policy enforcement and governance\n\n - APIs and developer tooling\n\n - And many other cool things!\n\nThis is platform engineering with product impact. Your systems will directly shape how customers build on top of AI. You’ll work closely with product, frontend, infra, and GTM to ship end-to-end features — not just tickets.\n\n\nWHAT YOU’LL DO\n\n - Design and build scalable backend services\n\n - Own major product surfaces from architecture to production\n\n - Improve reliability, performance, and developer experience\n\n - Work directly with customers to understand pain points\n\n - Ship enterprise-grade features without enterprise slowness\n\n - Use AI tooling aggressively — we expect you to automate yourself\n\n\nYOU MIGHT BE A FIT IF\n\n - You like building real products, not just infrastructure for infrastructure’s sake\n\n - You enjoy driving initiatives across teams to get things done\n\n - You think in terms of systems, tradeoffs, and business impact\n\n - You care about developer experience and clean abstractions\n\n - You’re curious about AI and want to build where the future is going\n\n - You want ownership, not task lists\n\n\nMINIMUM QUALIFICATIONS\n\n - Comfortable collaborating with both humans and AI systems (Yes, We’re Serious)\n\n - 5+ years of experience helping humans solve real problems\n\n - 2+ years of working with AI — agents, bots, chats, or building on top of models\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"ece226e2-2880-48a8-b51a-2ee2c039d3af","title":"Senior GTM Recruiter","department":"G&A","team":"Recruiting","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-03-31T20:20:04.924+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/ece226e2-2880-48a8-b51a-2ee2c039d3af","applyUrl":"https://jobs.ashbyhq.com/fireworks/ece226e2-2880-48a8-b51a-2ee2c039d3af/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We're looking for a strategic and hands-on Senior GTM Recruiter to join our growing People team and help fuel our next phase of growth. In this role, you'll own full-cycle recruiting for Go-To-Market functions — including Sales, Marketing and Partnerships — partnering closely with GTM leaders to build world-class teams that can take Fireworks' platform to market.
This isn't just a recruiting role, it's a chance to shape how an AI-native company hires. We're looking for someone who is genuinely excited about the AI industry, eager to experiment with AI-powered recruiting tools and workflows, and ready to help define what modern, intelligent talent acquisition looks like. If you love being at the forefront of both AI and hiring, this role was built for you.
Own full-cycle GTM recruitment across Sales, Marketing, Partnerships, Solutions Engineering, and Customer Success, with a focus on quality, speed, and candidate experience.
Partner with GTM hiring managers and executives to understand business needs, calibrate on candidate profiles, and develop targeted hiring strategies. Build and maintain talent pipelines and market maps for current and future needs.
Proactively source and engage high-caliber GTM talent through direct outreach, networking, referrals, and AI-powered sourcing platforms.
Collaborate with HRBPs, Compensation, and other People functions to align on role design, comp benchmarking, and market intelligence to inform hiring plans.
Champion AI-native recruiting practices, from sourcing automation and outreach personalization to pipeline analytics, while optimizing recruiting operations and tooling for a scalable, inclusive process.
5+ years of hands-on recruiting experience, ideally in fast-paced, high-growth environments.
Proven track record recruiting for GTM roles across Sales, Marketing and Partnerships.
Demonstrated ability to partner with founders, hiring managers, and senior GTM leaders to shape and influence hiring strategy.
Strong sourcing and candidate engagement skills, with a knack for identifying and activating top GTM talent.
Ability to work with urgency while maintaining high quality standards and a thoughtful candidate experience.
Experience scaling GTM teams at a startup or hypergrowth company, ideally in AI, infrastructure, or developer tools.
Familiarity with compensation structures and equity benchmarking in early-stage startups.
Hands-on experience with AI recruiting tools, whether that's AI-assisted sourcing, automated outreach, or workflow automation, and genuine enthusiasm to explore what's next.
Experience with Talent Operations to implement and optimize recruiting tools, systems, and workflows.
You're passionate about the AI industry. Not just as a recruiter operating in it, but as someone who follows it, thinks about it, and is excited to be part of building it. You see AI as a tool that makes you a better recruiter, not a threat to the craft. You're curious, experimental, and energized by figuring out how to do things better and faster. You bring that same energy to finding and closing exceptional GTM talent.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE\n\nWe're looking for a strategic and hands-on Senior GTM Recruiter to join our growing People team and help fuel our next phase of growth. In this role, you'll own full-cycle recruiting for Go-To-Market functions — including Sales, Marketing and Partnerships — partnering closely with GTM leaders to build world-class teams that can take Fireworks' platform to market.\n\nThis isn't just a recruiting role, it's a chance to shape how an AI-native company hires. We're looking for someone who is genuinely excited about the AI industry, eager to experiment with AI-powered recruiting tools and workflows, and ready to help define what modern, intelligent talent acquisition looks like. If you love being at the forefront of both AI and hiring, this role was built for you.\n\n\nKEY RESPONSIBILITIES\n\n - Own full-cycle GTM recruitment across Sales, Marketing, Partnerships, Solutions Engineering, and Customer Success, with a focus on quality, speed, and candidate experience.\n\n - Partner with GTM hiring managers and executives to understand business needs, calibrate on candidate profiles, and develop targeted hiring strategies. Build and maintain talent pipelines and market maps for current and future needs.\n\n - Proactively source and engage high-caliber GTM talent through direct outreach, networking, referrals, and AI-powered sourcing platforms.\n\n - Collaborate with HRBPs, Compensation, and other People functions to align on role design, comp benchmarking, and market intelligence to inform hiring plans.\n\n - Champion AI-native recruiting practices, from sourcing automation and outreach personalization to pipeline analytics, while optimizing recruiting operations and tooling for a scalable, inclusive process.\n\n\nMINIMUM QUALIFICATIONS\n\n - 5+ years of hands-on recruiting experience, ideally in fast-paced, high-growth environments.\n\n - Proven track record recruiting for GTM roles across Sales, Marketing and Partnerships.\n\n - Demonstrated ability to partner with founders, hiring managers, and senior GTM leaders to shape and influence hiring strategy.\n\n - Strong sourcing and candidate engagement skills, with a knack for identifying and activating top GTM talent.\n\n - Ability to work with urgency while maintaining high quality standards and a thoughtful candidate experience.\n\n\nPREFERRED QUALIFICATIONS\n\n - Experience scaling GTM teams at a startup or hypergrowth company, ideally in AI, infrastructure, or developer tools.\n\n - Familiarity with compensation structures and equity benchmarking in early-stage startups.\n\n - Hands-on experience with AI recruiting tools, whether that's AI-assisted sourcing, automated outreach, or workflow automation, and genuine enthusiasm to explore what's next.\n\n - Experience with Talent Operations to implement and optimize recruiting tools, systems, and workflows.\n\n\nWHO YOU ARE (BEYOND THE RESUME)\n\nYou're passionate about the AI industry. Not just as a recruiter operating in it, but as someone who follows it, thinks about it, and is excited to be part of building it. You see AI as a tool that makes you a better recruiter, not a threat to the craft. You're curious, experimental, and energized by figuring out how to do things better and faster. You bring that same energy to finding and closing exceptional GTM talent.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"94953c3a-cfc6-4cd0-9332-5e63ab91eb05","title":"Member of Technical Staff, Data Platform Engineer","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-04-07T19:03:33.849+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/94953c3a-cfc6-4cd0-9332-5e63ab91eb05","applyUrl":"https://jobs.ashbyhq.com/fireworks/94953c3a-cfc6-4cd0-9332-5e63ab91eb05/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We are looking for a Data Platform Engineer that specializes in Order-to-Cash (OTC) Revenue Transformation and AI Application Enablement to own and evolve the end-to-end billing, revenue and business data pipeline - from usage metering and invoice generation through revenue recognition and financial reporting. You will sit at the intersection of Engineering, Finance, and Data, ensuring every dollar of usage across our five revenue streams is accurately captured, billed, recognized, and reconciled.
This is a high-impact, cross-functional role. You will work hands-on with our billing platform (Orb, etc), accounting systems , data warehouse (BigQuery), and cloud marketplaces (AWS, GCP) — and ultimately help design AI-enabled workflow agents that automate reconciliation, anomaly detection, and revenue operations once the core data infrastructure is hardened.
Own and enhance billing infrastructure: pricing models, usage ingestion, invoicing, and revenue workflows.
Resolve key platform gaps (pricing flexibility, account hierarchy, overages, prepaid/credit logic).
Integrate billing with ERP, payments, and cloud marketplaces for an automated invoice-to-ledger pipeline.
Implement deferred revenue and prepaid amortization across all billing models.
Build and maintain an end-to-end OTC data pipeline (usage → billing → payments → revenue → GL → reporting).
Establish authoritative data models and ensure transaction-level reconciliation across all systems.
Implement data quality, auditability, and SOX-ready controls.
Strengthen CRM → Billing → ERP integration as a single source of truth.
Automate journal entries, AR sub-ledger, and revenue postings; integrate payments and marketplace settlements.
Build and deploy autonomous enterprise agents to automate and augment OTC operations, including anomaly detection, reconciliation, revenue recognition, collections, contract interpretation, and forecasting.
5+ years in billing engineering, revenue systems, or order-to-cash operations at a SaaS or usage-based platform company.
Experience with Billing Systems, ERP, AWS, K8, etc
Strong SQL and BigQuery proficiency — you can design schemas, write complex analytical queries, build dbt models, and maintain production data pipelines.
Working knowledge of accounting systems (QuickBooks or NetSuite) and the ability to map billing events to GL journal entries, manage sub-ledger reconciliation, and support month-end close.
Experience with payment platforms including payment processing, dunning, refunds, and cash application.
Familiarity with cloud marketplace billing — AWS Marketplace CPPO/SaaS contracts, GCP Marketplace, or Azure Marketplace private offers and settlement reporting.
Proficiency in Python or Node.js for building integrations, data transforms, and automation scripts.
Experience building LLM-powered agents or automation workflows — using frameworks like LangChain, or custom tool-calling architectures.
Background in GPU compute or AI infrastructure billing — understanding of compute-hour metering, token-based pricing, and capacity reservation models.
Experience with ERP migration projects (e.g., QuickBooks to NetSuite).
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE\n\nWe are looking for a Data Platform Engineer that specializes in Order-to-Cash (OTC) Revenue Transformation and AI Application Enablement to own and evolve the end-to-end billing, revenue and business data pipeline - from usage metering and invoice generation through revenue recognition and financial reporting. You will sit at the intersection of Engineering, Finance, and Data, ensuring every dollar of usage across our five revenue streams is accurately captured, billed, recognized, and reconciled.\n\nThis is a high-impact, cross-functional role. You will work hands-on with our billing platform (Orb, etc), accounting systems , data warehouse (BigQuery), and cloud marketplaces (AWS, GCP) — and ultimately help design AI-enabled workflow agents that automate reconciliation, anomaly detection, and revenue operations once the core data infrastructure is hardened.\n\n\nWHAT YOU'LL DO\n\n\nPHASE 1 – PLATFORM & DATA FOUNDATION\n\n - Own and enhance billing infrastructure: pricing models, usage ingestion, invoicing, and revenue workflows.\n\n - Resolve key platform gaps (pricing flexibility, account hierarchy, overages, prepaid/credit logic).\n\n - Integrate billing with ERP, payments, and cloud marketplaces for an automated invoice-to-ledger pipeline.\n\n - Implement deferred revenue and prepaid amortization across all billing models.\n\n - Build and maintain an end-to-end OTC data pipeline (usage → billing → payments → revenue → GL → reporting).\n\n - Establish authoritative data models and ensure transaction-level reconciliation across all systems.\n\n - Implement data quality, auditability, and SOX-ready controls.\n\n - Strengthen CRM → Billing → ERP integration as a single source of truth.\n\n - Automate journal entries, AR sub-ledger, and revenue postings; integrate payments and marketplace settlements.\n\n\nPHASE 2 – AUTONOMOUS INTELLIGENCE\n\n - Build and deploy autonomous enterprise agents to automate and augment OTC operations, including anomaly detection, reconciliation, revenue recognition, collections, contract interpretation, and forecasting. \n\n\n \n\n\nWHAT WE'RE LOOKING FOR\n\n\nPREFERRED\n\n - 5+ years in billing engineering, revenue systems, or order-to-cash operations at a SaaS or usage-based platform company.\n\n - Experience with Billing Systems, ERP, AWS, K8, etc\n\n - Strong SQL and BigQuery proficiency — you can design schemas, write complex analytical queries, build dbt models, and maintain production data pipelines.\n\n - Working knowledge of accounting systems (QuickBooks or NetSuite) and the ability to map billing events to GL journal entries, manage sub-ledger reconciliation, and support month-end close.\n\n - Experience with payment platforms including payment processing, dunning, refunds, and cash application.\n\n - Familiarity with cloud marketplace billing — AWS Marketplace CPPO/SaaS contracts, GCP Marketplace, or Azure Marketplace private offers and settlement reporting.\n\n - Proficiency in Python or Node.js for building integrations, data transforms, and automation scripts.\n\n - Experience building LLM-powered agents or automation workflows — using frameworks like LangChain, or custom tool-calling architectures.\n\n - Background in GPU compute or AI infrastructure billing — understanding of compute-hour metering, token-based pricing, and capacity reservation models.\n\n - Experience with ERP migration projects (e.g., QuickBooks to NetSuite).\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"1e8064d8-27ed-41b9-9d7a-1f9129e24ce0","title":"AI Native Account Executive","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-04-30T17:22:11.848+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/1e8064d8-27ed-41b9-9d7a-1f9129e24ce0","applyUrl":"https://jobs.ashbyhq.com/fireworks/1e8064d8-27ed-41b9-9d7a-1f9129e24ce0/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
Fireworks is building the fastest and most scalable generative AI platform in the world. We help leading startups and enterprises deploy open-source and custom LLMs in production with best-in-class performance, latency, and cost efficiency. Backed by Sequoia, Lightspeed, and Benchmark, Fireworks is trusted by GenAI-native companies like Cursor, Vercel, Genspark, and others across healthcare, finance, and developer tooling. We’re past $300M+ ARR and growing fast. Join us to define how GenAI gets adopted in the real world.
We’re hiring an AI Native Account Executive to drive adoption of Fireworks within the most ambitious GenAI startups. You’ll engage deeply with technical founders, ML leads, and product teams — helping them understand how Fireworks fits into their stack and guiding them through evaluation, onboarding, and scale-up. This isn’t a traditional transactional sales role: we’re looking for someone who can speak credibly to technical teams, identify high-impact use cases, and relentlessly pursue value creation for the customer. You’ll work cross-functionally with GTM engineers, product, and applied ML to unblock adoption, accelerate time to value, and grow usage in your accounts.
Own a portfolio of GenAI-native startup accounts and drive adoption across key use cases
Actively identify, engage, and qualify new high-potential prospects through warm outreach, events, and network-driven channels
Lead technical and product conversations with founders, ML engineers, and infra leads
Help customers get live quickly by coordinating onboarding, benchmarking, and integration efforts
Work closely with internal teams to shape tailored solutions, POCs, and fine-tuning approaches
Translate customer feedback into actionable insights for the product and engineering teams
Track account health and usage data to identify expansion opportunities
Be a visible representative of Fireworks in the GenAI ecosystem — including attending demo days, meetups, and online communities
Have 3+ years of experience in sales, business development, customer success, or product roles focused on technical buyers
Thrive in fast-moving environments and love engaging with startup founders and builders
Can understand and explain technical topics like open source inference, API performance, model tuning, or GPU architecture
Are proactive, persistent, and creative in breaking into accounts and building relationships
Have strong communication skills and can earn trust with both engineers and executives
Want to be on the front lines of the GenAI movement and work closely with companies shaping the future
Work directly with some of the most innovative GenAI startups in the world
Join a lean, high-impact GTM team where your work directly drives company growth
Build lasting relationships and help startups get real value from powerful infrastructure
Collaborate with world-class engineers and operators building at the bleeding edge of AI
Competitive base salary, strong equity, and long-term upside
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nABOUT THE ROLE\n\nFireworks is building the fastest and most scalable generative AI platform in the world. We help leading startups and enterprises deploy open-source and custom LLMs in production with best-in-class performance, latency, and cost efficiency. Backed by Sequoia, Lightspeed, and Benchmark, Fireworks is trusted by GenAI-native companies like Cursor, Vercel, Genspark, and others across healthcare, finance, and developer tooling. We’re past $300M+ ARR and growing fast. Join us to define how GenAI gets adopted in the real world.\n\n \n\nWe’re hiring an AI Native Account Executive to drive adoption of Fireworks within the most ambitious GenAI startups. You’ll engage deeply with technical founders, ML leads, and product teams — helping them understand how Fireworks fits into their stack and guiding them through evaluation, onboarding, and scale-up. This isn’t a traditional transactional sales role: we’re looking for someone who can speak credibly to technical teams, identify high-impact use cases, and relentlessly pursue value creation for the customer. You’ll work cross-functionally with GTM engineers, product, and applied ML to unblock adoption, accelerate time to value, and grow usage in your accounts.\n\n\nRESPONSIBILITIES\n\n - Own a portfolio of GenAI-native startup accounts and drive adoption across key use cases\n\n - Actively identify, engage, and qualify new high-potential prospects through warm outreach, events, and network-driven channels\n\n - Lead technical and product conversations with founders, ML engineers, and infra leads\n\n - Help customers get live quickly by coordinating onboarding, benchmarking, and integration efforts\n\n - Work closely with internal teams to shape tailored solutions, POCs, and fine-tuning approaches\n\n - Translate customer feedback into actionable insights for the product and engineering teams\n\n - Track account health and usage data to identify expansion opportunities\n\n - Be a visible representative of Fireworks in the GenAI ecosystem — including attending demo days, meetups, and online communities\n\n\nYOU MIGHT BE A FIT IF YOU\n\n - Have 3+ years of experience in sales, business development, customer success, or product roles focused on technical buyers\n\n - Thrive in fast-moving environments and love engaging with startup founders and builders\n\n - Can understand and explain technical topics like open source inference, API performance, model tuning, or GPU architecture\n\n - Are proactive, persistent, and creative in breaking into accounts and building relationships\n\n - Have strong communication skills and can earn trust with both engineers and executives\n\n - Want to be on the front lines of the GenAI movement and work closely with companies shaping the future\n\n\nWHY FIREWORKS\n\n - Work directly with some of the most innovative GenAI startups in the world\n\n - Join a lean, high-impact GTM team where your work directly drives company growth\n\n - Build lasting relationships and help startups get real value from powerful infrastructure\n\n - Collaborate with world-class engineers and operators building at the bleeding edge of AI\n\n - Competitive base salary, strong equity, and long-term upside\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"3e1d1451-5535-4da7-89be-52fddb48109a","title":"Revenue Accounting Lead","department":"G&A","team":"Finance","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-05-19T00:08:54.917+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/3e1d1451-5535-4da7-89be-52fddb48109a","applyUrl":"https://jobs.ashbyhq.com/fireworks/3e1d1451-5535-4da7-89be-52fddb48109a/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We are seeking a highly motivated and detail-oriented Revenue Accounting Lead to join our Finance organization. This role will own and scale the company’s revenue accounting processes, ensure compliance with ASC 606, and partner cross-functionally with Sales, Legal, FP&A, Deal Desk, and Operations to support the company’s rapid growth.
This is an excellent opportunity for someone who thrives in a fast-paced environment, enjoys building scalable processes, and wants to make a meaningful impact at a high-growth AI company.
Lead all aspects of revenue accounting operations, including contract review, revenue recognition, deferred revenue, and month-end close activities
Ensure compliance with ASC 606 and maintain accurate revenue recognition policies and documentation
Review customer contracts and collaborate with Legal and Sales Operations to determine accounting implications for complex deal structures
Prepare and review revenue-related journal entries, reconciliations, and reporting schedules
Partner closely with FP&A to support forecasting, ARR/MRR reporting, and SaaS metrics analysis
Drive automation and process improvements across quote-to-cash and revenue close workflows
Support external audits, including preparation of revenue accounting memos and audit schedules
Develop and maintain scalable internal controls related to revenue processes and systems
Collaborate with Billing, Collections, and GTM teams to improve operational efficiency and data integrity
Assist with implementation and optimization of ERP and revenue systems
Build scalable policies and infrastructure to support international expansion and evolving product offerings
Mentor and guide junior accounting team members as the organization grows
Bachelor’s degree in Accounting or Finance; CPA strongly preferred
6+ years of progressive accounting experience, including revenue accounting in a SaaS or technology company
Strong understanding of ASC 606 and SaaS revenue recognition concepts
Experience reviewing complex customer contracts and translating accounting guidance into operational execution
Strong analytical skills and attention to detail
Experience working in high-growth startup or fast-scaling environments preferred
Familiarity with ERP systems such as NetSuite and revenue automation tools such as Stripe, Orb, or Zuora
Ability to communicate effectively across technical and non-technical teams
Self-starter with strong project management and organizational skills
Comfortable navigating ambiguity and building processes from the ground up
Experience in AI, cloud infrastructure, consumption-based pricing, or usage-based billing models
Experience supporting IPO readiness or SOX compliance initiatives
Prior public accounting experience, preferably within a Big Four firm
Experience managing or mentoring team members
Opportunity to help shape the financial foundation of a rapidly growing AI company
High-impact role with visibility across Finance and executive leadership
Collaborative and mission-driven culture
Competitive compensation, equity, and benefits
Flexible and hybrid-friendly work environment
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nWe are seeking a highly motivated and detail-oriented Revenue Accounting Lead to join our Finance organization. This role will own and scale the company’s revenue accounting processes, ensure compliance with ASC 606, and partner cross-functionally with Sales, Legal, FP&A, Deal Desk, and Operations to support the company’s rapid growth.\n\nThis is an excellent opportunity for someone who thrives in a fast-paced environment, enjoys building scalable processes, and wants to make a meaningful impact at a high-growth AI company.\n\n\nWHAT YOU’LL DO\n\n - Lead all aspects of revenue accounting operations, including contract review, revenue recognition, deferred revenue, and month-end close activities\n\n - Ensure compliance with ASC 606 and maintain accurate revenue recognition policies and documentation\n\n - Review customer contracts and collaborate with Legal and Sales Operations to determine accounting implications for complex deal structures\n\n - Prepare and review revenue-related journal entries, reconciliations, and reporting schedules\n\n - Partner closely with FP&A to support forecasting, ARR/MRR reporting, and SaaS metrics analysis\n\n - Drive automation and process improvements across quote-to-cash and revenue close workflows\n\n - Support external audits, including preparation of revenue accounting memos and audit schedules\n\n - Develop and maintain scalable internal controls related to revenue processes and systems\n\n - Collaborate with Billing, Collections, and GTM teams to improve operational efficiency and data integrity\n\n - Assist with implementation and optimization of ERP and revenue systems\n\n - Build scalable policies and infrastructure to support international expansion and evolving product offerings\n\n - Mentor and guide junior accounting team members as the organization grows\n\n\nWHAT WE’RE LOOKING FOR\n\n - Bachelor’s degree in Accounting or Finance; CPA strongly preferred\n\n - 6+ years of progressive accounting experience, including revenue accounting in a SaaS or technology company\n\n - Strong understanding of ASC 606 and SaaS revenue recognition concepts\n\n - Experience reviewing complex customer contracts and translating accounting guidance into operational execution\n\n - Strong analytical skills and attention to detail\n\n - Experience working in high-growth startup or fast-scaling environments preferred\n\n - Familiarity with ERP systems such as NetSuite and revenue automation tools such as Stripe, Orb, or Zuora\n\n - Ability to communicate effectively across technical and non-technical teams\n\n - Self-starter with strong project management and organizational skills\n\n - Comfortable navigating ambiguity and building processes from the ground up\n\n\nNICE TO HAVE\n\n - Experience in AI, cloud infrastructure, consumption-based pricing, or usage-based billing models\n\n - Experience supporting IPO readiness or SOX compliance initiatives\n\n - Prior public accounting experience, preferably within a Big Four firm\n\n - Experience managing or mentoring team members\n\n\nWHY JOIN US\n\n - Opportunity to help shape the financial foundation of a rapidly growing AI company\n\n - High-impact role with visibility across Finance and executive leadership\n\n - Collaborative and mission-driven culture\n\n - Competitive compensation, equity, and benefits\n\n - Flexible and hybrid-friendly work environment\n\n \n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"e47bf56b-2696-48b2-93fc-11fd1263906c","title":"Field Marketing Manager, Startups","department":"Marketing","team":"Marketing","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-05-22T18:24:43.417+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/e47bf56b-2696-48b2-93fc-11fd1263906c","applyUrl":"https://jobs.ashbyhq.com/fireworks/e47bf56b-2696-48b2-93fc-11fd1263906c/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
This is a new role within the Fireworks AI Marketing team, key to driving our pipeline efforts within events and creating a program for startup founders and early-stage operators. You’ll own the community, content, and marketing programs needed to build a vibrant, active, and engaged founder/operator network—one that shares startup journeys and best practices, provides product feedback internally, and champions Fireworks as an essential tool for early-stage teams. If you're a passionate field and experiential marketer looking for an opportunity to create extraordinary in-person experiences and build from the ground up, this is your chance to create innovative programs that directly shape Fireworks AI's brand experience in SF.
You'll collaborate closely with cross-functional stakeholders in sales and customer success, delivering events that bolster the AMER sales team. You'll partner with our product marketing, creative studio, partner, devrel, and demand generation teams to develop high-value events. These in-person experiences will provide top-notch content and experiences for our customers and prospects.
Create top notch experiences to delight customers and prospects, with a guest-first approach to creating field events and experiences that bring our brand and product to life.
Own end-to-end planning, execution, vendors, budgets, timelines of all event and field programs, including executive dinners, roundtables. workshops, trade-shows, and co-sponsored partner activations.
Drive measurable pipeline and revenue impact from every program
Develop pre-event, day-of, and post-event engagement strategies that maximize registration-to-attendance conversion and sales follow-up
Work hand-in-hand with sales teams to build targeted invite lists and ensure strong attendance from priority accounts
Track and report on program ROI to make recommendations on how we invest in field events to drive incremental business impact.
5 + years of field marketing or event marketing experience in B2B SaaS
A passion for all things field and experiential marketing. You understand the purpose and place for all types of events - executive events, tradeshows, networking events - taking pride in delivering on the finest of details that make the difference between a good event and a great event.
Are a strong cross-functional collaborator who can work effectively with Sales, Partnerships, Creative, Communications, and executive stakeholders
Experience working cross functionally with sales leadership, sales representatives, customer success, creative, content, and product marketing.
Proficient in CRM and marketing automation software, must is Salesforce
Experience at a startup or hyper-growth company is preferred; especially within the Bay Area
Experience in startup marketing (B2B startup / founder-led GTM) is a plus
Experience delivering both in-person field events & larger scale user conferences
Familiarity with the AI/ML landscape and how developer and enterprise teams are adopting AI solutions.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nABOUT THE ROLE:\n\nThis is a new role within the Fireworks AI Marketing team, key to driving our pipeline efforts within events and creating a program for startup founders and early-stage operators. You’ll own the community, content, and marketing programs needed to build a vibrant, active, and engaged founder/operator network—one that shares startup journeys and best practices, provides product feedback internally, and champions Fireworks as an essential tool for early-stage teams. If you're a passionate field and experiential marketer looking for an opportunity to create extraordinary in-person experiences and build from the ground up, this is your chance to create innovative programs that directly shape Fireworks AI's brand experience in SF.\n\nYou'll collaborate closely with cross-functional stakeholders in sales and customer success, delivering events that bolster the AMER sales team. You'll partner with our product marketing, creative studio, partner, devrel, and demand generation teams to develop high-value events. These in-person experiences will provide top-notch content and experiences for our customers and prospects.\n\n\nKEY RESPONSIBILITIES:\n\n - Create top notch experiences to delight customers and prospects, with a guest-first approach to creating field events and experiences that bring our brand and product to life.\n\n - Own end-to-end planning, execution, vendors, budgets, timelines of all event and field programs, including executive dinners, roundtables. workshops, trade-shows, and co-sponsored partner activations.\n\n - Drive measurable pipeline and revenue impact from every program\n\n - Develop pre-event, day-of, and post-event engagement strategies that maximize registration-to-attendance conversion and sales follow-up\n\n - Work hand-in-hand with sales teams to build targeted invite lists and ensure strong attendance from priority accounts\n\n - Track and report on program ROI to make recommendations on how we invest in field events to drive incremental business impact.\n\n\nSKILLS YOU'LL NEED TO BRING:\n\n - 5 + years of field marketing or event marketing experience in B2B SaaS\n\n - A passion for all things field and experiential marketing. You understand the purpose and place for all types of events - executive events, tradeshows, networking events - taking pride in delivering on the finest of details that make the difference between a good event and a great event.\n\n - Are a strong cross-functional collaborator who can work effectively with Sales, Partnerships, Creative, Communications, and executive stakeholders\n\n - Experience working cross functionally with sales leadership, sales representatives, customer success, creative, content, and product marketing.\n\n - Proficient in CRM and marketing automation software, must is Salesforce\n\n\nNICE TO HAVES:\n\n - Experience at a startup or hyper-growth company is preferred; especially within the Bay Area\n\n - Experience in startup marketing (B2B startup / founder-led GTM) is a plus\n\n - Experience delivering both in-person field events & larger scale user conferences\n\n - Familiarity with the AI/ML landscape and how developer and enterprise teams are adopting AI solutions.\n\n \n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"2b9193ea-dbff-40b1-a766-0f872665c7fe","title":"Sr Field Marketing Manager ","department":"Marketing","team":"Marketing","employmentType":"FullTime","location":"San Francisco Bay Area","secondaryLocations":[],"publishedAt":"2026-05-22T18:22:44.769+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/fireworks/2b9193ea-dbff-40b1-a766-0f872665c7fe","applyUrl":"https://jobs.ashbyhq.com/fireworks/2b9193ea-dbff-40b1-a766-0f872665c7fe/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
This is a senior, high-impact role on Fireworks AI's Marketing team, central to our pipeline strategy and go-to-market motion. As a Senior Field Marketing Manager, you'll be a key architect of how we show up in the field, owning a mix of strategy, execution of our event and field programs, while helping establish the foundational infrastructure and playbooks that will scale the team.
If you're a passionate field and experiential marketer looking for an opportunity to create extraordinary in-person experiences and build from the ground up, this is your chance to create innovative events that directly shape Fireworks AI's brand experience on the West Coast or East Coast. You're not just running events — you're building a repeatable engine for pipeline and brand.
You'll collaborate closely with cross-functional stakeholders in sales and leadership to design experiences that accelerate deals and deepen customer relationships. You'll bring a strategic lens to audience segmentation, investment decisions, and program measurement, while also rolling up your sleeves to execute.
Develop Fireworks AI's east coast field marketing strategy, aligning program investments to sales priorities, pipeline goals, and key customer segments.
Conceptualize and produce end to end planning, execution, of hosted events including executive experiences, large-format educational events, trade shows, co-sponsored activations, and flagship user conferences.
Build pre-event, day-of, and post-event engagement strategies that maximize registration-to-attendance conversion and drive strong sales follow-up.
Partner with sales leadership on territory and account-level strategy, ensuring field programs reach the right accounts at the right moments in the buying cycle.
Track and report on program ROI to marketing and sales leadership, making data-driven recommendations on how we invest in field events to drive incremental business impact.
Mentor and provide guidance to junior field marketing team members as the function grows.
7+ years of field marketing or event marketing experience in B2B SaaS or B2B tech.
A passion for all things field and experiential marketing. You understand the purpose and place for every event type, from executive dinners to trade shows, and take pride in the details that elevate a good event to a great one.
A strong strategic instinct paired with operational excellence: you can zoom out to define a program roadmap and zoom in to manage the logistics that make the difference.
Experience partnering with sales leadership and AEs to develop territory-level event strategies and account-based marketing motions.
Proven ability to manage complex, multi-event portfolios simultaneously across diverse program types
Strong cross-functional collaborator who works effectively with Sales, Partnerships, Creative, Communications, and executive stakeholders.
Strong written and verbal communication skills, including the ability to create clear event documentation and present post-event insights to leadership.
Comfortable with data and analytics, using event metrics to optimize programs and clearly demonstrate ROI.
Proficiency in CRM and marketing automation software; Salesforce is required.
Experience at a startup or hyper-growth company is preferred; especially within the Bay Area
Experience delivering both in-person field events and larger-scale user conferences, including flagship events (500+ attendees).
Background designing and optimizing account-based marketing (ABM) motions in partnership with demand generation teams.
Marketo experience.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nABOUT THE ROLE:\n\nThis is a senior, high-impact role on Fireworks AI's Marketing team, central to our pipeline strategy and go-to-market motion. As a Senior Field Marketing Manager, you'll be a key architect of how we show up in the field, owning a mix of strategy, execution of our event and field programs, while helping establish the foundational infrastructure and playbooks that will scale the team.\n\nIf you're a passionate field and experiential marketer looking for an opportunity to create extraordinary in-person experiences and build from the ground up, this is your chance to create innovative events that directly shape Fireworks AI's brand experience on the West Coast or East Coast. You're not just running events — you're building a repeatable engine for pipeline and brand.\n\nYou'll collaborate closely with cross-functional stakeholders in sales and leadership to design experiences that accelerate deals and deepen customer relationships. You'll bring a strategic lens to audience segmentation, investment decisions, and program measurement, while also rolling up your sleeves to execute.\n\n\nKEY RESPONSIBILITIES:\n\n - Develop Fireworks AI's east coast field marketing strategy, aligning program investments to sales priorities, pipeline goals, and key customer segments.\n\n - Conceptualize and produce end to end planning, execution, of hosted events including executive experiences, large-format educational events, trade shows, co-sponsored activations, and flagship user conferences.\n\n - Build pre-event, day-of, and post-event engagement strategies that maximize registration-to-attendance conversion and drive strong sales follow-up.\n\n - Partner with sales leadership on territory and account-level strategy, ensuring field programs reach the right accounts at the right moments in the buying cycle.\n\n - Track and report on program ROI to marketing and sales leadership, making data-driven recommendations on how we invest in field events to drive incremental business impact.\n\n - Mentor and provide guidance to junior field marketing team members as the function grows.\n\n\nSKILLS YOU'LL NEED TO BRING:\n\n - 7+ years of field marketing or event marketing experience in B2B SaaS or B2B tech.\n\n - A passion for all things field and experiential marketing. You understand the purpose and place for every event type, from executive dinners to trade shows, and take pride in the details that elevate a good event to a great one.\n\n - A strong strategic instinct paired with operational excellence: you can zoom out to define a program roadmap and zoom in to manage the logistics that make the difference.\n\n - Experience partnering with sales leadership and AEs to develop territory-level event strategies and account-based marketing motions.\n\n - Proven ability to manage complex, multi-event portfolios simultaneously across diverse program types\n\n - Strong cross-functional collaborator who works effectively with Sales, Partnerships, Creative, Communications, and executive stakeholders.\n\n - Strong written and verbal communication skills, including the ability to create clear event documentation and present post-event insights to leadership.\n\n - Comfortable with data and analytics, using event metrics to optimize programs and clearly demonstrate ROI.\n\n - Proficiency in CRM and marketing automation software; Salesforce is required.\n\n\nNICE TO HAVES:\n\n - Experience at a startup or hyper-growth company is preferred; especially within the Bay Area\n\n - Experience delivering both in-person field events and larger-scale user conferences, including flagship events (500+ attendees).\n\n - Background designing and optimizing account-based marketing (ABM) motions in partnership with demand generation teams.\n\n - Marketo experience.\n\n \n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"0e175af6-e53a-4e48-91ba-db3aaef8dac7","title":"Head of Marketing Operations","department":"Marketing","team":"Marketing","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-05-27T22:28:00.456+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/0e175af6-e53a-4e48-91ba-db3aaef8dac7","applyUrl":"https://jobs.ashbyhq.com/fireworks/0e175af6-e53a-4e48-91ba-db3aaef8dac7/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
The Head of Marketing Operations builds the infrastructure that lets Fireworks marketing scale, and runs the operating system that keeps the team performing day to day. You own the marketing tech stack, the data model, the lifecycle, and the analytics that turn marketing into a predictable pipeline engine that the executive team can trust. You also own the planning rhythms, budget, prioritization, and program management that keep every function inside marketing shipping on time and in sync.
The right person is rigorous, opinionated about tooling, and energized by the operational problems most marketers avoid. You think about marketing the way a great operator thinks about a business: cadence, accountability, resource allocation, and clear measurement.
This role is remote-friendly within the US. You will travel to our San Mateo HQ periodically for team onsites, planning sessions, and key moments that benefit from being in person. We will establish a cadence that works for the team and the role.
You own the marketing tech stack end-to-end: selection, implementation, integration, and the standards that govern how data flows between systems. This includes the marketing automation platform, CDP or warehouse-native architecture decisions, enrichment, and the integration layer with Salesforce. Success is measured by stack reliability, total cost of ownership, and the speed at which marketing can launch new programs.
You run the operating rhythm of the marketing team. This includes the annual and quarterly planning process, goal setting and tracking, weekly business reviews, and cross-functional program management across demand gen, product marketing, content, and brand. You own the marketing budget model, vendor contracts, headcount planning support, and the prioritization framework that turns a long list of ideas into a focused roadmap. You are the connective tissue that makes the rest of the marketing team faster, more aligned, and easier to scale. Success is measured by on-time program delivery, budget accuracy, and team velocity.
You own the full lifecycle from anonymous visitor through closed-won, including lead scoring, MQL and PQL definitions, SLA enforcement, and the handoff to sales. This includes the operational rigor around routing, nurture, and re-engagement. Success is measured by SDR conversion lift and clean handoff metrics.
You own marketing analytics, attribution methodology, and the dashboards that the executive team and the board see. This includes pipeline attribution, channel ROI, and the quarterly marketing performance review. Success is measured by leadership confidence in the numbers and by speed of decision-making informed by them.
You own data hygiene, privacy compliance (GDPR, CCPA, and emerging US state laws), and the governance model that keeps our database trustworthy as we scale. Success is measured by data quality scores, deliverability rates, and zero material compliance incidents.
Marketing-sourced pipeline is reported with confidence and audit-ready definitions
Lead scoring drives measurable lift in downstream conversion rates
The full funnel from visitor to closed-won is instrumented and visible in shared dashboards
Campaign launch time drops as a result of better operational playbooks
Marketing and sales agree on the data, the definitions, and the single source of truth
The marketing team operates on a clear quarterly cadence with shared priorities, transparent budget, and on-time delivery against the plan
The SVP of Marketing and the broader exec team have real-time visibility into team capacity, program status, and spend without chasing updates
Campaign creative and execution: Demand Gen leader
Sales technology and territory design: Sales Operations
Product analytics and PLG instrumentation: Product and Data teams
8+ years in marketing operations with at least 3 years in a leadership role
Experience building marketing operations from scratch or replatforming at a B2B SaaS company
Proven track record at a startup or fast-scaling growth-stage company
Track record running planning cadences, OKRs, and cross-functional program management for a marketing org
Deep fluency in HubSpot or Marketo, Salesforce, and at least one BI tool (Looker, Tableau, Sigma)
Comfort owning data quality, GDPR/CCPA compliance, and attribution debates
Experience managing budget, vendor relationships, and headcount planning alongside a marketing leader
Calm under pressure with strong opinions held loosely
Past experience at a developer-first or product-led growth company
SQL fluency
Experience with hybrid PQL and MQL scoring models
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nABOUT THIS ROLE\n\nThe Head of Marketing Operations builds the infrastructure that lets Fireworks marketing scale, and runs the operating system that keeps the team performing day to day. You own the marketing tech stack, the data model, the lifecycle, and the analytics that turn marketing into a predictable pipeline engine that the executive team can trust. You also own the planning rhythms, budget, prioritization, and program management that keep every function inside marketing shipping on time and in sync.\n\nThe right person is rigorous, opinionated about tooling, and energized by the operational problems most marketers avoid. You think about marketing the way a great operator thinks about a business: cadence, accountability, resource allocation, and clear measurement.\n\n\nLOCATION AND WORK STYLE\n\nThis role is remote-friendly within the US. You will travel to our San Mateo HQ periodically for team onsites, planning sessions, and key moments that benefit from being in person. We will establish a cadence that works for the team and the role.\n\n\nRESPONSIBILITIES\n\n\nMARKETING TECHNOLOGY STACK AND ARCHITECTURE\n\nYou own the marketing tech stack end-to-end: selection, implementation, integration, and the standards that govern how data flows between systems. This includes the marketing automation platform, CDP or warehouse-native architecture decisions, enrichment, and the integration layer with Salesforce. Success is measured by stack reliability, total cost of ownership, and the speed at which marketing can launch new programs.\n\n\nMARKETING OPERATING SYSTEM AND PROGRAM MANAGEMENT\n\nYou run the operating rhythm of the marketing team. This includes the annual and quarterly planning process, goal setting and tracking, weekly business reviews, and cross-functional program management across demand gen, product marketing, content, and brand. You own the marketing budget model, vendor contracts, headcount planning support, and the prioritization framework that turns a long list of ideas into a focused roadmap. You are the connective tissue that makes the rest of the marketing team faster, more aligned, and easier to scale. Success is measured by on-time program delivery, budget accuracy, and team velocity.\n\n\nLIFECYCLE, LEAD MANAGEMENT, AND SCORING\n\nYou own the full lifecycle from anonymous visitor through closed-won, including lead scoring, MQL and PQL definitions, SLA enforcement, and the handoff to sales. This includes the operational rigor around routing, nurture, and re-engagement. Success is measured by SDR conversion lift and clean handoff metrics.\n\n\nATTRIBUTION, REPORTING, AND ANALYTICS\n\nYou own marketing analytics, attribution methodology, and the dashboards that the executive team and the board see. This includes pipeline attribution, channel ROI, and the quarterly marketing performance review. Success is measured by leadership confidence in the numbers and by speed of decision-making informed by them.\n\n\nDATA GOVERNANCE AND COMPLIANCE\n\nYou own data hygiene, privacy compliance (GDPR, CCPA, and emerging US state laws), and the governance model that keeps our database trustworthy as we scale. Success is measured by data quality scores, deliverability rates, and zero material compliance incidents.\n\n\nWHAT SUCCESS LOOKS LIKE\n\n - Marketing-sourced pipeline is reported with confidence and audit-ready definitions\n\n - Lead scoring drives measurable lift in downstream conversion rates\n\n - The full funnel from visitor to closed-won is instrumented and visible in shared dashboards\n\n - Campaign launch time drops as a result of better operational playbooks\n\n - Marketing and sales agree on the data, the definitions, and the single source of truth\n\n - The marketing team operates on a clear quarterly cadence with shared priorities, transparent budget, and on-time delivery against the plan\n\n - The SVP of Marketing and the broader exec team have real-time visibility into team capacity, program status, and spend without chasing updates\n\n\nWHAT THIS ROLE DOES NOT OWN\n\n - Campaign creative and execution: Demand Gen leader\n\n - Sales technology and territory design: Sales Operations\n\n - Product analytics and PLG instrumentation: Product and Data teams\n\n\nYOU SHOULD HAVE\n\n - 8+ years in marketing operations with at least 3 years in a leadership role\n\n - Experience building marketing operations from scratch or replatforming at a B2B SaaS company\n\n - Proven track record at a startup or fast-scaling growth-stage company\n\n - Track record running planning cadences, OKRs, and cross-functional program management for a marketing org\n\n - Deep fluency in HubSpot or Marketo, Salesforce, and at least one BI tool (Looker, Tableau, Sigma)\n\n - Comfort owning data quality, GDPR/CCPA compliance, and attribution debates\n\n - Experience managing budget, vendor relationships, and headcount planning alongside a marketing leader\n\n - Calm under pressure with strong opinions held loosely\n\n\nNICE TO HAVE\n\n - Past experience at a developer-first or product-led growth company\n\n - SQL fluency\n\n - Experience with hybrid PQL and MQL scoring models\n\n \n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"38aa9926-2865-45c4-ac38-585b78ee68ac","title":"Member of Technical Staff- Full Stack Software Engineer","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-05T17:30:24.380+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/38aa9926-2865-45c4-ac38-585b78ee68ac","applyUrl":"https://jobs.ashbyhq.com/fireworks/38aa9926-2865-45c4-ac38-585b78ee68ac/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We are looking for a Full Stack Software Engineering to architect, build, and scale our developer-focused web application (fireworks.ai) and shape our end-to-end technical architecture. This role blends hands-on engineering with technical leadership, offering the opportunity to mentor other engineers, collaborate cross-functionally, and drive innovation in a fast-paced, AI-focused environment.
You'll play a key role in delivering scalable, elegant, and highly performant solutions that directly impact our hundreds of thousands of developers and product vision. You will be directly shaping and shipping the most optimal developer journey—spanning intuitive front-end interfaces, robust APIs, and efficient backend orchestration—combined with our large offering of open-source generative AI models, enabling our users to seamlessly build, experiment, and ship their AI workflows with our playground.
End-to-End Ownership: Engineering ownership of fireworks.ai from the user interface down to the API and data layer, with a strong focus on a delightful developer journey.
Product-Led Growth: Participate in the team’s shared accountability for product-led growth through the web application, model playground, and seamless user onboarding workflows.
Full Stack Development: Design, develop, and test responsive, performant web applications alongside robust, scalable backend services and APIs.
Leadership & Mentorship: Mentor and support a team of full stack, frontend, and backend engineers through code reviews, pair programming, and ongoing technical coaching.
Architectural Excellence: Define and implement full stack architectural standards, API design best practices, database schemas, and modern development workflows.
Cross-Functional Collaboration: Partner with Product, Design, and Core AI/Infrastructure Engineering to align on requirements, system design, timelines, and delivery expectations.
Systems & Components: Build and maintain reusable, scalable frontend component libraries while ensuring backend services are modular and easily integrated.
Unified Developer Experience: Partner with other engineering teams to build an aligned developer journey across web, SDK, and CLI surfaces.
Quality & Performance: Champion application performance, security, data integrity, and accessibility across the entire software stack.
Innovation: Drive innovation by staying informed of emerging full stack trends, cloud-native technologies, and AI orchestration frameworks.
Education: Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
Experience: 6+ years of professional experience in full stack software development.
Leadership: 2+ years of experience in a technical leadership role (e.g., tech lead, team lead, or engineering manager).
Frontend Proficiency: Strong expertise in React, TypeScript, JavaScript, and Next.js.
Backend Proficiency: Strong expertise in building server-side applications, designing RESTful or GraphQL APIs, and working with modern backend languages (e.g., Node.js, Python, Go).
Data Management: Solid understanding of database systems (SQL/NoSQL), caching strategies, and data modeling.
Track Record: Proven track record of delivering and scaling production-grade, full stack web applications.
Architecture & Devops: Experience with modern cloud infrastructure (AWS, GCP, or OCI), containerization (Docker), and full stack CI/CD pipelines.
AI/ML Domain Knowledge: Experience working in AI/ML-focused environments, or interacting with LLM APIs, vector databases, and model orchestration tools (e.g., LangChain, LlamaIndex).
Startup Agility: Prior startup experience—especially as a technical founder or early engineer—is a major plus.
People Growth: Experience managing or mentoring other engineers, including providing performance feedback and supporting career development.
Developer Tooling: Prior experience building developer platforms, SaaS dashboards, or complex interactive environments like playgrounds and sandboxes.
Open Source: Contributions to open-source projects, internal component libraries, or developer tools.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE\n\nWe are looking for a Full Stack Software Engineering to architect, build, and scale our developer-focused web application (fireworks.ai) and shape our end-to-end technical architecture. This role blends hands-on engineering with technical leadership, offering the opportunity to mentor other engineers, collaborate cross-functionally, and drive innovation in a fast-paced, AI-focused environment.\n\nYou'll play a key role in delivering scalable, elegant, and highly performant solutions that directly impact our hundreds of thousands of developers and product vision. You will be directly shaping and shipping the most optimal developer journey—spanning intuitive front-end interfaces, robust APIs, and efficient backend orchestration—combined with our large offering of open-source generative AI models, enabling our users to seamlessly build, experiment, and ship their AI workflows with our playground.\n\n\nKEY RESPONSIBILITIES\n\n - End-to-End Ownership: Engineering ownership of fireworks.ai from the user interface down to the API and data layer, with a strong focus on a delightful developer journey.\n\n - Product-Led Growth: Participate in the team’s shared accountability for product-led growth through the web application, model playground, and seamless user onboarding workflows.\n\n - Full Stack Development: Design, develop, and test responsive, performant web applications alongside robust, scalable backend services and APIs.\n\n - Leadership & Mentorship: Mentor and support a team of full stack, frontend, and backend engineers through code reviews, pair programming, and ongoing technical coaching.\n\n - Architectural Excellence: Define and implement full stack architectural standards, API design best practices, database schemas, and modern development workflows.\n\n - Cross-Functional Collaboration: Partner with Product, Design, and Core AI/Infrastructure Engineering to align on requirements, system design, timelines, and delivery expectations.\n\n - Systems & Components: Build and maintain reusable, scalable frontend component libraries while ensuring backend services are modular and easily integrated.\n\n - Unified Developer Experience: Partner with other engineering teams to build an aligned developer journey across web, SDK, and CLI surfaces.\n\n - Quality & Performance: Champion application performance, security, data integrity, and accessibility across the entire software stack.\n\n - Innovation: Drive innovation by staying informed of emerging full stack trends, cloud-native technologies, and AI orchestration frameworks.\n\n\nMINIMUM QUALIFICATIONS\n\n - Education: Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.\n\n - Experience: 6+ years of professional experience in full stack software development.\n\n - Leadership: 2+ years of experience in a technical leadership role (e.g., tech lead, team lead, or engineering manager).\n\n - Frontend Proficiency: Strong expertise in React, TypeScript, JavaScript, and Next.js.\n\n - Backend Proficiency: Strong expertise in building server-side applications, designing RESTful or GraphQL APIs, and working with modern backend languages (e.g., Node.js, Python, Go).\n\n - Data Management: Solid understanding of database systems (SQL/NoSQL), caching strategies, and data modeling.\n\n - Track Record: Proven track record of delivering and scaling production-grade, full stack web applications.\n\n - Architecture & Devops: Experience with modern cloud infrastructure (AWS, GCP, or OCI), containerization (Docker), and full stack CI/CD pipelines.\n\n\nPREFERRED QUALIFICATIONS\n\n - AI/ML Domain Knowledge: Experience working in AI/ML-focused environments, or interacting with LLM APIs, vector databases, and model orchestration tools (e.g., LangChain, LlamaIndex).\n\n - Startup Agility: Prior startup experience—especially as a technical founder or early engineer—is a major plus.\n\n - People Growth: Experience managing or mentoring other engineers, including providing performance feedback and supporting career development.\n\n - Developer Tooling: Prior experience building developer platforms, SaaS dashboards, or complex interactive environments like playgrounds and sandboxes.\n\n - Open Source: Contributions to open-source projects, internal component libraries, or developer tools.\n\n\n\n\n\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"a2a1cdd0-c79c-4023-b8ba-3c1349aedbdb","title":"AI Native - Strategic, Account Executive","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-05T17:31:22.687+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/a2a1cdd0-c79c-4023-b8ba-3c1349aedbdb","applyUrl":"https://jobs.ashbyhq.com/fireworks/a2a1cdd0-c79c-4023-b8ba-3c1349aedbdb/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We’re hiring an AI Native - Strategic Pursuits Account Executive to drive adoption of Fireworks within the most ambitious and strategic AI companies. This isn’t a traditional sales role: we’re looking for someone who can speak credibly to technical teams, identify high-impact use cases, and relentlessly pursue value creation for the customer. We are looking for highly motivated, networked, and technically adept individuals to serve as trusted advisors to our most important customers and prospects.
You’ll engage deeply with technical founders, ML leads, and product teams, helping them understand how Fireworks fits into their stack and guiding them through evaluation, onboarding, and scale-up. You’ll work in lockstep with our Applied AI team on key accounts, partner with product and ML specialists to architect the right technical approach, and run a clean commercial cycle with our GTM partners. You’ll be the quarterback of the account from initial POC through production at scale.
Technical Partnership & Execution
Lead technical and product discovery and conversations with founders, ML engineers, and infra leads.
Work closely with Field Engineering, Applied AI, Product and Research teams to shape tailored solutions, POCs, and fine-tuning approaches.
Translate customer feedback into actionable insights for Fireworks product and engineering with specificity and urgency.
Help customers get live quickly by coordinating onboarding, benchmarking, and integration efforts.
Deal Management & Commercial Execution
Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.
Manage multiple concurrent accounts with fast iteration cycles. Prioritize ruthlessly, keep scope tight, and maintain momentum.
Structure and negotiate complex commercial terms.
Actively identify, engage, and qualify new prospects through executive and investor networks, industry events, and partnerships.
Run a disciplined operating cadence with your portfolio of customers: reviewing key trends, driving outcomes, and jointly planning the next phase of the partnership.
Executive Alignment and Ecosystem Presence
Own the relationship with key Strategic AI Native accounts, from first engagement through production deployment. Earn trust with ML engineers and Founders in the same meeting.
Nurture and shape strong executive relationships.
Be a visible representative of Fireworks in the AI startup ecosystem.
Have 7+ years of experience as a PM, strategic account executive, VC,, or previous management consulting experience focused on serving highly technical buyers and portfolio companies
Demonstrated ability to run multi-threaded customer engagements: mapping stakeholders, managing commercial cycles, and maintaining deal and relationship momentum
Technical fluency to lead discovery with ML engineers and infrastructure leads and ability to discuss open-source vs. proprietary models, model tuning, reserved capacity, and compliance requirements
Thrive in fast-moving environments and love engaging with leading startup founders and builders
Are proactive, persistent, and creative in breaking into accounts and building lasting relationships throughout the organization
Have strong communication skills and can earn trust with both engineers and executives
Want to be on the front lines of the AI movement and work closely with companies shaping the future
Help define AI Native Strategic Pursuits go-to-market for one of the fastest-growing AI infrastructure companies in the world
Work directly with the most innovative AI startups
Join a lean, high-impact GTM team where your work drives outsized influence on company trajectory
Build lasting relationships and help startups get real value from best-in-class infrastructure
Collaborate with world class engineers and operators building at the bleeding edge of AI
Competitive salary, equity in a fast-growing startup, comprehensive benefits package, and long-term upside
Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.
OTE Pay Range (Plus Equity)
$280,000-$320,000 USD; 50/50 split + Stock Options
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nABOUT THE ROLE\n\nWe’re hiring an AI Native - Strategic Pursuits Account Executive to drive adoption of Fireworks within the most ambitious and strategic AI companies. This isn’t a traditional sales role: we’re looking for someone who can speak credibly to technical teams, identify high-impact use cases, and relentlessly pursue value creation for the customer. We are looking for highly motivated, networked, and technically adept individuals to serve as trusted advisors to our most important customers and prospects. \n\nYou’ll engage deeply with technical founders, ML leads, and product teams, helping them understand how Fireworks fits into their stack and guiding them through evaluation, onboarding, and scale-up. You’ll work in lockstep with our Applied AI team on key accounts, partner with product and ML specialists to architect the right technical approach, and run a clean commercial cycle with our GTM partners. You’ll be the quarterback of the account from initial POC through production at scale. \n\n\nRESPONSIBILITIES\n\nTechnical Partnership & Execution\n\n - Lead technical and product discovery and conversations with founders, ML engineers, and infra leads.\n\n - Work closely with Field Engineering, Applied AI, Product and Research teams to shape tailored solutions, POCs, and fine-tuning approaches.\n\n - Translate customer feedback into actionable insights for Fireworks product and engineering with specificity and urgency.\n\n - Help customers get live quickly by coordinating onboarding, benchmarking, and integration efforts.\n\nDeal Management & Commercial Execution\n\n - Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.\n\n - Manage multiple concurrent accounts with fast iteration cycles. Prioritize ruthlessly, keep scope tight, and maintain momentum.\n\n - Structure and negotiate complex commercial terms.\n\n - Actively identify, engage, and qualify new prospects through executive and investor networks, industry events, and partnerships.\n\n - Run a disciplined operating cadence with your portfolio of customers: reviewing key trends, driving outcomes, and jointly planning the next phase of the partnership.\n\nExecutive Alignment and Ecosystem Presence\n\n - Own the relationship with key Strategic AI Native accounts, from first engagement through production deployment. Earn trust with ML engineers and Founders in the same meeting.\n\n - Nurture and shape strong executive relationships.\n\n - Be a visible representative of Fireworks in the AI startup ecosystem.\n\n\nYOU MIGHT BE A FIT IF YOU\n\n - Have 7+ years of experience as a PM, strategic account executive, VC,, or previous management consulting experience focused on serving highly technical buyers and portfolio companies\n\n - Demonstrated ability to run multi-threaded customer engagements: mapping stakeholders, managing commercial cycles, and maintaining deal and relationship momentum \n\n - Technical fluency to lead discovery with ML engineers and infrastructure leads and ability to discuss open-source vs. proprietary models, model tuning, reserved capacity, and compliance requirements\n\n - Thrive in fast-moving environments and love engaging with leading startup founders and builders\n\n - Are proactive, persistent, and creative in breaking into accounts and building lasting relationships throughout the organization \n\n - Have strong communication skills and can earn trust with both engineers and executives\n\n - Want to be on the front lines of the AI movement and work closely with companies shaping the future\n\n\nWHY FIREWORKS\n\n - Help define AI Native Strategic Pursuits go-to-market for one of the fastest-growing AI infrastructure companies in the world\n\n - Work directly with the most innovative AI startups \n\n - Join a lean, high-impact GTM team where your work drives outsized influence on company trajectory\n\n - Build lasting relationships and help startups get real value from best-in-class infrastructure\n\n - Collaborate with world class engineers and operators building at the bleeding edge of AI\n\n - Competitive salary, equity in a fast-growing startup, comprehensive benefits package, and long-term upside\n\nBase salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.\n\nOTE Pay Range (Plus Equity)\n\n$280,000-$320,000 USD; 50/50 split + Stock Options\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"1fc5eb25-08ad-4c82-aaee-5b903b9ab0ea","title":"AI Field Engineer, Singapore","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"Singapore","secondaryLocations":[],"publishedAt":"2026-07-23T01:49:33.870+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Singapore","addressCountry":"Singapore","addressLocality":"Singapore"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/1fc5eb25-08ad-4c82-aaee-5b903b9ab0ea","applyUrl":"https://jobs.ashbyhq.com/fireworks/1fc5eb25-08ad-4c82-aaee-5b903b9ab0ea/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
The Role
AI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes.
You spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call.
The Segment
As a Field Engineer in the Enterprise track you will work with large organizations and digital-native companies adopting GenAI across the business. These engagements span more stakeholders and longer cycles, so you will manage executive relationships and align teams while staying hands-on in the code. The emphasis is on pairing strong technical delivery with the executive presence to earn trust across an org: discovery, solution design, POC execution, and the path to production at enterprise scale.
What You'll Work On
Technical Delivery and Deployment
Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.
For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.
Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets
Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.
Model Strategy and Fine-Tuning
Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.
Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.
Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores.
Customer Engagement and Stakeholder Management
Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge.
Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.
Own the technical relationship from first engagement through production deployment. Earn trust with ML engineers and VPs in the same meeting.
Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens.
Product Feedback and Platform Improvement
Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features.
Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself.
Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency.
What We're Looking For
Minimum Qualifications
5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.
Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.
Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).
Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.
Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.
Preferred Qualifications
10+ years in technical field or engineering roles.
Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.
Experience operating as a technical authority inside a customer's environment building within their infrastructure, navigating their constraints, and shipping code that runs in their production systems.
Track record taking GenAI POCs from prototype to production-scale deployments.
Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex).
Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nThe Role\n\nAI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes.\n\nYou spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call.\n\nThe Segment\n\nAs a Field Engineer in the Enterprise track you will work with large organizations and digital-native companies adopting GenAI across the business. These engagements span more stakeholders and longer cycles, so you will manage executive relationships and align teams while staying hands-on in the code. The emphasis is on pairing strong technical delivery with the executive presence to earn trust across an org: discovery, solution design, POC execution, and the path to production at enterprise scale.\n\nWhat You'll Work On\n\nTechnical Delivery and Deployment\n\n - Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.\n\n - For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.\n\n - Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets\n\n - Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.\n\nModel Strategy and Fine-Tuning\n\n - Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.\n\n - Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.\n\n - Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores.\n\nCustomer Engagement and Stakeholder Management\n\n - Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge.\n\n - Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.\n\n - Own the technical relationship from first engagement through production deployment. Earn trust with ML engineers and VPs in the same meeting.\n\n - Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens.\n\nProduct Feedback and Platform Improvement\n\n - Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features.\n\n - Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself.\n\n - Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency.\n\nWhat We're Looking For\n\nMinimum Qualifications\n\n - 5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.\n\n - Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.\n\n - Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.\n\n - Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).\n\n - Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.\n\n - Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.\n\nPreferred Qualifications\n\n - 10+ years in technical field or engineering roles.\n\n - Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.\n\n - Experience operating as a technical authority inside a customer's environment building within their infrastructure, navigating their constraints, and shipping code that runs in their production systems.\n\n - Track record taking GenAI POCs from prototype to production-scale deployments.\n\n - Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex).\n\n - Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"504591e5-fccd-4a7f-a9ca-81b51d2a5a12","title":"AI Field Engineer, EMEA","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"London","secondaryLocations":[],"publishedAt":"2026-07-22T22:31:35.153+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"London","addressCountry":"United Kingdom","addressLocality":"London"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/504591e5-fccd-4a7f-a9ca-81b51d2a5a12","applyUrl":"https://jobs.ashbyhq.com/fireworks/504591e5-fccd-4a7f-a9ca-81b51d2a5a12/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
The Role
AI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes.
You spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call.
The Segment
As a Field Engineer in the Enterprise track you will work with large organizations and digital-native companies adopting GenAI across the business. These engagements span more stakeholders and longer cycles, so you will manage executive relationships and align teams while staying hands-on in the code. The emphasis is on pairing strong technical delivery with the executive presence to earn trust across an org: discovery, solution design, POC execution, and the path to production at enterprise scale.
What You'll Work On
Technical Delivery and Deployment
Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.
For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.
Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets
Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.
Model Strategy and Fine-Tuning
Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.
Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.
Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores.
Customer Engagement and Stakeholder Management
Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge.
Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.
Own the technical relationship from first engagement through production deployment. Earn trust with ML engineers and VPs in the same meeting.
Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens.
Product Feedback and Platform Improvement
Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features.
Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself.
Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency.
What We're Looking For
Minimum Qualifications
5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.
Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.
Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).
Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.
Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.
Preferred Qualifications
10+ years in technical field or engineering roles.
Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.
Experience operating as a technical authority inside a customer's environment building within their infrastructure, navigating their constraints, and shipping code that runs in their production systems.
Track record taking GenAI POCs from prototype to production-scale deployments.
Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex).
Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nThe Role\n\nAI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes.\n\nYou spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call.\n\nThe Segment\n\nAs a Field Engineer in the Enterprise track you will work with large organizations and digital-native companies adopting GenAI across the business. These engagements span more stakeholders and longer cycles, so you will manage executive relationships and align teams while staying hands-on in the code. The emphasis is on pairing strong technical delivery with the executive presence to earn trust across an org: discovery, solution design, POC execution, and the path to production at enterprise scale.\n\nWhat You'll Work On\n\nTechnical Delivery and Deployment\n\n - Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.\n\n - For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.\n\n - Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets\n\n - Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.\n\nModel Strategy and Fine-Tuning\n\n - Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.\n\n - Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.\n\n - Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores.\n\nCustomer Engagement and Stakeholder Management\n\n - Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge.\n\n - Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.\n\n - Own the technical relationship from first engagement through production deployment. Earn trust with ML engineers and VPs in the same meeting.\n\n - Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens.\n\nProduct Feedback and Platform Improvement\n\n - Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features.\n\n - Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself.\n\n - Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency.\n\nWhat We're Looking For\n\nMinimum Qualifications\n\n - 5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.\n\n - Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.\n\n - Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.\n\n - Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).\n\n - Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.\n\n - Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.\n\nPreferred Qualifications\n\n - 10+ years in technical field or engineering roles.\n\n - Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.\n\n - Experience operating as a technical authority inside a customer's environment building within their infrastructure, navigating their constraints, and shipping code that runs in their production systems.\n\n - Track record taking GenAI POCs from prototype to production-scale deployments.\n\n - Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex).\n\n - Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"e5a9746e-49ac-407f-b953-5cf3c08a7802","title":"Applied Machine Learning Engineer, EMEA","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"London","secondaryLocations":[],"publishedAt":"2026-07-23T01:17:50.806+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"London","addressCountry":"United Kingdom","addressLocality":"London"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/e5a9746e-49ac-407f-b953-5cf3c08a7802","applyUrl":"https://jobs.ashbyhq.com/fireworks/e5a9746e-49ac-407f-b953-5cf3c08a7802/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.
Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.
Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.
Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.
New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.
Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.
Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.
Bachelor’s degree in Computer Science, Engineering, or a related technical field.
5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.
Robust coding skills required, preferably with proficiency in Python.
Demonstrated ability to lead and execute complex technical projects with a focus on customer success.
Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.
Master’s degree in Computer Science, Engineering, or a related technical field.
Experience working in a startup or fast-paced environment.
Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).
Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nAs an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.\n\n\nKEY RESPONSIBILITIES:\n\n - Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.\n\n - Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.\n\n - Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.\n\n - Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.\n\n - New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.\n\n - Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.\n\n - Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.\n\n\nMINIMUM QUALIFICATIONS:\n\n - Bachelor’s degree in Computer Science, Engineering, or a related technical field.\n\n - 5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.\n\n - Robust coding skills required, preferably with proficiency in Python.\n\n - Demonstrated ability to lead and execute complex technical projects with a focus on customer success.\n\n - Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.\n\n\nPREFERRED QUALIFICATIONS:\n\n - Master’s degree in Computer Science, Engineering, or a related technical field.\n\n - Experience working in a startup or fast-paced environment.\n\n - Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).\n\n - Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"0e0c2c47-6aa2-4b8c-98f9-19fc51bc2ea2","title":"Enterprise Account Executive, Singapore","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"Singapore","secondaryLocations":[],"publishedAt":"2026-07-23T01:58:08.696+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"Singapore","addressCountry":"Singapore","addressLocality":"Singapore"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/0e0c2c47-6aa2-4b8c-98f9-19fc51bc2ea2","applyUrl":"https://jobs.ashbyhq.com/fireworks/0e0c2c47-6aa2-4b8c-98f9-19fc51bc2ea2/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We are seeking an experienced Enterprise Account Executive to join our sales team. The ideal candidate has a solid track record at early-stage startups, selling to technical stakeholders, and consistently exceeding quotas by closing six-figure deals. This role demands a driven individual capable of navigating the complexities of selling software solutions to large enterprises, with a keen understanding of the technical nuances involved.
Drive new business opportunities by developing and executing a sales strategy for selling Fireworks AI within targeted accounts
Gain a deep understanding of Fireworks AI's offerings and value proposition, effectively articulating them in the market
Focus on pipeline generation within your targeted accounts to ensure long-term success
Interact with and leverage the Channel and Alliance partner community to find new opportunities and drive existing deals to close
Manage the entire sales cycle from prospecting to procurement
Forecast accurately and leverage internal resources to hit your annual quota efficiently
Regularly update all active accounts, reporting on sales activities, status, and progress
Maintain a high level of customer satisfaction and referenceability
Travel for client visits and presentations as needed
Bachelor’s degree or equivalent years of working experience
5+ years of progressive SaaS software sales experience, with a proven \"hunter\" mentality
2+ years experience selling SaaS products to a technical audience
Demonstrated success in closing business in large complex enterprise accounts
Excellent negotiation, analytical, financial, and organizational skills, thriving in an evolving entrepreneurial environment
Outstanding verbal and written communication skills
Fireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in London, UK for this role is £200,000 - £240,000 per year.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nWe are seeking an experienced Enterprise Account Executive to join our sales team. The ideal candidate has a solid track record at early-stage startups, selling to technical stakeholders, and consistently exceeding quotas by closing six-figure deals. This role demands a driven individual capable of navigating the complexities of selling software solutions to large enterprises, with a keen understanding of the technical nuances involved.\n\n\nKEY RESPONSIBILITIES:\n\n - Drive new business opportunities by developing and executing a sales strategy for selling Fireworks AI within targeted accounts\n\n - Gain a deep understanding of Fireworks AI's offerings and value proposition, effectively articulating them in the market\n\n - Focus on pipeline generation within your targeted accounts to ensure long-term success\n\n - Interact with and leverage the Channel and Alliance partner community to find new opportunities and drive existing deals to close\n\n - Manage the entire sales cycle from prospecting to procurement\n\n - Forecast accurately and leverage internal resources to hit your annual quota efficiently\n\n - Regularly update all active accounts, reporting on sales activities, status, and progress\n\n - Maintain a high level of customer satisfaction and referenceability\n\n - Travel for client visits and presentations as needed\n\n\nMINIMUM REQUIREMENTS:\n\n - Bachelor’s degree or equivalent years of working experience \n\n - 5+ years of progressive SaaS software sales experience, with a proven \"hunter\" mentality\n\n - 2+ years experience selling SaaS products to a technical audience\n\n - Demonstrated success in closing business in large complex enterprise accounts\n\n - Excellent negotiation, analytical, financial, and organizational skills, thriving in an evolving entrepreneurial environment\n\n - Outstanding verbal and written communication skills\n\nFireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in London, UK for this role is £200,000 - £240,000 per year.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"58083381-6c71-4d58-9014-bd2bcb3e1e85","title":"Paid Growth Marketer","department":"Marketing","team":"Marketing","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-11T17:33:27.925+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/58083381-6c71-4d58-9014-bd2bcb3e1e85","applyUrl":"https://jobs.ashbyhq.com/fireworks/58083381-6c71-4d58-9014-bd2bcb3e1e85/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
About the Role
Fireworks is building one of the most important infrastructure platforms in AI. Just like frontier open-source inference enables sustainable unit economics for our customers, we are building a sustainable growth engine to drive demand gen for the Fireworks business. We're hiring a Paid Growth Marketer to lead all paid marketing programs across the full funnel, from awareness to engagement and activation.
This is a hands-on role. You'll manage multi-million dollar budgets with analytical rigor, build the measurement infrastructure that connects spend to pipeline, and develop Fireworks' internal capacity for structured paid experimentation. You'll also think strategically about where the paid landscape is heading and position us ahead of it.
You'll report into the Director of Growth and partner closely with Sales and Product to align paid programs with product launches, sales cycles, and ICP targeting. The ideal candidate will bring a strong growth mindset to everything they do, using AI as a productivity accelerant to move faster and operate more effectively than any traditional paid marketer could.
Responsibilities
Own paid strategy and execution across paid search, social, display, OOH, and developer-focused channels
Manage and optimize a multi-million dollar ad budget, with full accountability for efficiency and attributable pipeline.
Build and maintain attribution and measurement frameworks that connect spend to pipeline with real signal
Lead Fireworks' paid experimentation program — hypothesis, execution, readout, iteration
Partner with Sales, Product, and Finance teams to align paid programs with cross-functional dependencies.
Track the evolution of the advertising ecosystem and proactively build that thinking into our roadmap.
You Might Be a Fit If You
Have 6+ years of hands-on paid marketing experience, including direct ownership of multi-million dollar annual budgets
Have driven measurable, efficient growth for a B2B SaaS or developer-facing product(s)
Are analytically fluent and can pull your own data and share insights succinctly.
Have built and run structured experimentation programs within cross-functional teams
Actively use AI tools to accelerate your work and see that as a core part of how great marketers operate today
Communicate clearly and concisely: you can align a sales partner, brief a product manager, and update leadership without losing the thread
Adept at navigating ambiguity and bias to action; the paid playbook here is still being written and you're excited to write it
Preferred Qualifications
Experience marketing developer tools, APIs, or infrastructure products
Familiarity with the API inference provider ecosystem
Experience standing up or evolving marketing measurement infrastructure
Why Fireworks
Join a lean, high-impact marketing team where your work directly drives company growth
Own a meaningful budget and build programs from the ground up
Collaborate with world-class engineers, researchers, and operators at the frontier of AI
Competitive base salary, strong equity, and long-term upside
On Target Earnings (Plus Equity)
$160,000 - $190,000 USD
Total compensation also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nAbout the Role\n\nFireworks is building one of the most important infrastructure platforms in AI. Just like frontier open-source inference enables sustainable unit economics for our customers, we are building a sustainable growth engine to drive demand gen for the Fireworks business. We're hiring a Paid Growth Marketer to lead all paid marketing programs across the full funnel, from awareness to engagement and activation.\n\nThis is a hands-on role. You'll manage multi-million dollar budgets with analytical rigor, build the measurement infrastructure that connects spend to pipeline, and develop Fireworks' internal capacity for structured paid experimentation. You'll also think strategically about where the paid landscape is heading and position us ahead of it.\n\nYou'll report into the Director of Growth and partner closely with Sales and Product to align paid programs with product launches, sales cycles, and ICP targeting. The ideal candidate will bring a strong growth mindset to everything they do, using AI as a productivity accelerant to move faster and operate more effectively than any traditional paid marketer could.\n\nResponsibilities\n\n - Own paid strategy and execution across paid search, social, display, OOH, and developer-focused channels\n\n - Manage and optimize a multi-million dollar ad budget, with full accountability for efficiency and attributable pipeline.\n\n - Build and maintain attribution and measurement frameworks that connect spend to pipeline with real signal\n\n - Lead Fireworks' paid experimentation program — hypothesis, execution, readout, iteration\n\n - Partner with Sales, Product, and Finance teams to align paid programs with cross-functional dependencies.\n\n - Track the evolution of the advertising ecosystem and proactively build that thinking into our roadmap.\n\nYou Might Be a Fit If You\n\n - Have 6+ years of hands-on paid marketing experience, including direct ownership of multi-million dollar annual budgets\n\n - Have driven measurable, efficient growth for a B2B SaaS or developer-facing product(s)\n\n - Are analytically fluent and can pull your own data and share insights succinctly.\n\n - Have built and run structured experimentation programs within cross-functional teams\n\n - Actively use AI tools to accelerate your work and see that as a core part of how great marketers operate today\n\n - Communicate clearly and concisely: you can align a sales partner, brief a product manager, and update leadership without losing the thread\n\n - Adept at navigating ambiguity and bias to action; the paid playbook here is still being written and you're excited to write it\n\nPreferred Qualifications\n\n - Experience marketing developer tools, APIs, or infrastructure products\n\n - Familiarity with the API inference provider ecosystem\n\n - Experience standing up or evolving marketing measurement infrastructure\n\nWhy Fireworks\n\n - Join a lean, high-impact marketing team where your work directly drives company growth\n\n - Own a meaningful budget and build programs from the ground up\n\n - Collaborate with world-class engineers, researchers, and operators at the frontier of AI\n\n - Competitive base salary, strong equity, and long-term upside\n\nOn Target Earnings (Plus Equity)\n\n$160,000 - $190,000 USD\n\nTotal compensation also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"d37e5839-a4fb-4cf0-8e76-b1684d211da0","title":"Head of Sales Strategy & Analytics","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"San Francisco Bay Area","secondaryLocations":[],"publishedAt":"2026-06-11T17:56:53.566+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/fireworks/d37e5839-a4fb-4cf0-8e76-b1684d211da0","applyUrl":"https://jobs.ashbyhq.com/fireworks/d37e5839-a4fb-4cf0-8e76-b1684d211da0/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
Our GTM organization is scaling fast and needs a strategic and analytical foundation to match. In this role you will lead our Sales Strategy and Revenue Analytics pillars, reporting to the VP of Revenue Operations. This role requires someone who has operated in a consumption or usage-based business and understands how that changes forecasting, territory design, and what good GTM metrics actually look like.
You'll own the foundation the GTM org runs on: operating model, territory and coverage design, revenue and GPU forecasting, QBR/WBR operating cadence, and the repeatable sales motions that turn annual strategy into quarterly execution. You'll be a strategic partner to sales leadership and a connector across Sales, Finance, Data, and Product.
You'll set the operating model, defend it with data, and change it when the business changes. We want someone who measures their impact in decisions changed, not decks delivered.
Own how the GTM organization is structured to win: segment coverage, territory design, rules of engagement across GTM and Product, and quota-setting philosophy. Translate annual targets into territory plans that give every rep a fair book and every segment the right level of coverage. Revisit and adjust as the business evolves.
Build and own the forecasting process across bookings, renewals, and consumption in partnership with Finance, Sales, and Data. Establish a methodology that works for a business where committed ARR and consumption expansion behave differently. Deliver forecasts leadership can trust, with clear variance explanation and recommended actions.
Run the QBR, WBR, and planning forums that keep the GTM organization aligned, accountable, and moving. Design the cadence, own the agenda, and make sure the output is decisions and actions, not status updates. Act as a strategic advisor to GTM leaders, surfacing pipeline risk and growth opportunity before it shows up in results.
Define and execute a consistent sales process across account planning, territory planning, and pipeline generation. Turn what works into a playbook. Instrument it so performance is visible, coaching is targeted, and the team gets better over time.
10+ years in Revenue Strategy, Sales Strategy, Sales Operations, or Revenue Operations at B2B companies
Has owned an end-to-end forecasting process, not just contributed to one
Has designed territory and quota models at scale
Has built and led a team with direct reports across strategy or analytics functions
Strong analytical foundation: can build a model from scratch, not just interpret one
Experience at a usage-based, consumption, or API-first company
Has run strategy and operations across both enterprise and PLG/product-led motions simultaneously
Comfortable presenting to CFO, board, and executive team with well-reasoned variance analysis
Has worked at an AI/ML infrastructure, developer tools, or high-growth technical B2B company
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE\n\nOur GTM organization is scaling fast and needs a strategic and analytical foundation to match. In this role you will lead our Sales Strategy and Revenue Analytics pillars, reporting to the VP of Revenue Operations. This role requires someone who has operated in a consumption or usage-based business and understands how that changes forecasting, territory design, and what good GTM metrics actually look like.\n\nYou'll own the foundation the GTM org runs on: operating model, territory and coverage design, revenue and GPU forecasting, QBR/WBR operating cadence, and the repeatable sales motions that turn annual strategy into quarterly execution. You'll be a strategic partner to sales leadership and a connector across Sales, Finance, Data, and Product.\n\nYou'll set the operating model, defend it with data, and change it when the business changes. We want someone who measures their impact in decisions changed, not decks delivered.\n\n\nWHAT YOU'LL OWN\n\n\n1. GTM OPERATING MODEL AND TERRITORY/ROE DESIGN\n\nOwn how the GTM organization is structured to win: segment coverage, territory design, rules of engagement across GTM and Product, and quota-setting philosophy. Translate annual targets into territory plans that give every rep a fair book and every segment the right level of coverage. Revisit and adjust as the business evolves.\n\n\n2. REVENUE AND GPU FORECASTING\n\nBuild and own the forecasting process across bookings, renewals, and consumption in partnership with Finance, Sales, and Data. Establish a methodology that works for a business where committed ARR and consumption expansion behave differently. Deliver forecasts leadership can trust, with clear variance explanation and recommended actions.\n\n\n3. BUSINESS PARTNERSHIP AND OPERATING CADENCE\n\nRun the QBR, WBR, and planning forums that keep the GTM organization aligned, accountable, and moving. Design the cadence, own the agenda, and make sure the output is decisions and actions, not status updates. Act as a strategic advisor to GTM leaders, surfacing pipeline risk and growth opportunity before it shows up in results.\n\n\n4. SALES PROCESS INTO REPEATABLE MOTIONS\n\nDefine and execute a consistent sales process across account planning, territory planning, and pipeline generation. Turn what works into a playbook. Instrument it so performance is visible, coaching is targeted, and the team gets better over time.\n\n\nMINIMUM QUALIFICATIONS\n\n - 10+ years in Revenue Strategy, Sales Strategy, Sales Operations, or Revenue Operations at B2B companies\n\n - Has owned an end-to-end forecasting process, not just contributed to one\n\n - Has designed territory and quota models at scale\n\n - Has built and led a team with direct reports across strategy or analytics functions\n\n - Strong analytical foundation: can build a model from scratch, not just interpret one\n\n\nPREFERRED QUALIFICATIONS\n\n - Experience at a usage-based, consumption, or API-first company\n\n - Has run strategy and operations across both enterprise and PLG/product-led motions simultaneously\n\n - Comfortable presenting to CFO, board, and executive team with well-reasoned variance analysis\n\n - Has worked at an AI/ML infrastructure, developer tools, or high-growth technical B2B company\n\n \n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"4a5dbfe4-b0d5-4394-a94b-42345fb425b4","title":"AI Field Engineer - Strategic Partnerships","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-11T18:19:24.929+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/4a5dbfe4-b0d5-4394-a94b-42345fb425b4","applyUrl":"https://jobs.ashbyhq.com/fireworks/4a5dbfe4-b0d5-4394-a94b-42345fb425b4/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
The Role
As an AI Field Engineer for Strategic Partnerships, you will be one of the technical owners of Fireworks' most strategic partnership. You’ll work closely with Strategic Partner field teams, Partner-aligned ISVs, and the SIs that run enterprise AI transformation programs to make Fireworks the default inference and fine-tuning layer in every Partner AI architecture. The role sits at the intersection of engineering, partner development, and customer delivery. You build reference architectures, run benchmarks, debug production integrations, and co-develop POCs — all while holding your own in executive-level conversations about strategy, roadmap, and business outcomes.
You spend most of your time building and enabling. You ship code, run joint POCs with Partner field teams, and architect deployments that span Strategic Partners and Fireworks. But you also lead discovery conversations, align partner stakeholders, and translate field signals into product improvements that compress the feedback loop from partner to roadmap.
The Segment
As a Field Engineer aligned with our Partnerships team you own the technical relationship between Fireworks and the Partner ecosystems, Partner field teams, ISVs building on Strategic Partners, and the SIs that deliver AI transformation programs on Strategic Partners. As an example, the Microsoft partnership is a core go-to-market bet: clients like UIPath, Stack Blitz, Motif run via Fireworks on Foundry.. Your job is to scale that pattern across the partner ecosystem. These engagements involve large, multi-stakeholder organizations, so you will need to navigate both the enterprise buyer (IT, security, compliance) and the builder (ML engineers, platform teams, app developers), while building the trusted-advisor relationships inside Microsoft's field that multiply your reach.
What You'll Work On
Technical Delivery and Deployment
Be the technical lead on co-sell motions with Strategic Partners — joint reference architectures, partner integration patterns, and shared POCs for strategic accounts.
Build end-to-end POCs and MVPs alongside partner engineering teams, working inside their codebases, infrastructure, and constraints.
Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets.
Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.
Model Strategy and Fine-Tuning
Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.
Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.
Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores
Product Feedback and Platform Improvement
Own the feedback loop — surface partner-driven product gaps to Fireworks engineering, and translate the roadmap back into partner messaging.
Ship external technical content: reference architectures, integration guides, and benchmark posts that make it easy for partners to win deals with us.
Track pipeline health; flag risks and opportunities to Field leadership weekly
What We're Looking For:
Minimum Qualifications
3+ years in a pre-sales, partner engineering, forward-deployed, or technical consulting role.
Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.
Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.
Hands-on fluency with LLM inference: latency/throughput tradeoffs, batching strategies, quantization, structured outputs, function calling. You can explain why 50ms p99 matters to an enterprise CTO.
Real experience with fine-tuning — LoRA at minimum, RFT a strong plus. You understand when SFT is enough and when it isn't.
Deep familiarity with the Azure AI stack: Azure Foundry, Azure OpenAI Service, Azure ML, AKS, Entra/RBAC for AI workloads. You know where Fireworks fits and where it doesn't.
Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.
Preferred Qualifications
5+ years in technical field or engineering roles where you've owned a technical relationship with a hyperscaler or major SI, not just supported one
Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.
Prior role at a hyperscaler, AI-native cloud, or inference provider.
Deep familiarity with other strategic partner stacks: Platforms for AI workloads, network, and identity integration patterns. You know where Fireworks fits and where it doesn't.
Experience with agentic frameworks (LangChain, LlamaIndex, or custom tool-use pipelines) — you understand how inference latency and reliability shapes agent behavior at scale.
Background in model evaluation — you understand why benchmark gaming is rampant and what rigorous evals actually look like.
You've written a technical blog post or reference architecture that people actually read.
Track record taking GenAI POCs from prototype to production-scale deployments.
On-Target Expectations (Plus Equity)
$200,000 - $260,000 USD
Total compensation also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nThe Role\n\nAs an AI Field Engineer for Strategic Partnerships, you will be one of the technical owners of Fireworks' most strategic partnership. You’ll work closely with Strategic Partner field teams, Partner-aligned ISVs, and the SIs that run enterprise AI transformation programs to make Fireworks the default inference and fine-tuning layer in every Partner AI architecture. The role sits at the intersection of engineering, partner development, and customer delivery. You build reference architectures, run benchmarks, debug production integrations, and co-develop POCs — all while holding your own in executive-level conversations about strategy, roadmap, and business outcomes.\n\nYou spend most of your time building and enabling. You ship code, run joint POCs with Partner field teams, and architect deployments that span Strategic Partners and Fireworks. But you also lead discovery conversations, align partner stakeholders, and translate field signals into product improvements that compress the feedback loop from partner to roadmap.\n\nThe Segment\n\nAs a Field Engineer aligned with our Partnerships team you own the technical relationship between Fireworks and the Partner ecosystems, Partner field teams, ISVs building on Strategic Partners, and the SIs that deliver AI transformation programs on Strategic Partners. As an example, the Microsoft partnership is a core go-to-market bet: clients like UIPath, Stack Blitz, Motif run via Fireworks on Foundry.. Your job is to scale that pattern across the partner ecosystem. These engagements involve large, multi-stakeholder organizations, so you will need to navigate both the enterprise buyer (IT, security, compliance) and the builder (ML engineers, platform teams, app developers), while building the trusted-advisor relationships inside Microsoft's field that multiply your reach.\n\nWhat You'll Work On\n\nTechnical Delivery and Deployment\n\n - Be the technical lead on co-sell motions with Strategic Partners — joint reference architectures, partner integration patterns, and shared POCs for strategic accounts.\n\n - Build end-to-end POCs and MVPs alongside partner engineering teams, working inside their codebases, infrastructure, and constraints.\n\n - Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets.\n\n - Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.\n\nModel Strategy and Fine-Tuning\n\n - Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.\n\n - Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.\n\n - Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores\n\nProduct Feedback and Platform Improvement\n\n - Own the feedback loop — surface partner-driven product gaps to Fireworks engineering, and translate the roadmap back into partner messaging.\n\n - Ship external technical content: reference architectures, integration guides, and benchmark posts that make it easy for partners to win deals with us.\n\n - Track pipeline health; flag risks and opportunities to Field leadership weekly\n\nWhat We're Looking For:\n\nMinimum Qualifications\n\n - 3+ years in a pre-sales, partner engineering, forward-deployed, or technical consulting role.\n\n - Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.\n\n - Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.\n\n - Hands-on fluency with LLM inference: latency/throughput tradeoffs, batching strategies, quantization, structured outputs, function calling. You can explain why 50ms p99 matters to an enterprise CTO.\n\n - Real experience with fine-tuning — LoRA at minimum, RFT a strong plus. You understand when SFT is enough and when it isn't.\n\n - Deep familiarity with the Azure AI stack: Azure Foundry, Azure OpenAI Service, Azure ML, AKS, Entra/RBAC for AI workloads. You know where Fireworks fits and where it doesn't.\n\n - Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.\n\nPreferred Qualifications\n\n - 5+ years in technical field or engineering roles where you've owned a technical relationship with a hyperscaler or major SI, not just supported one\n\n - Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.\n\n - Prior role at a hyperscaler, AI-native cloud, or inference provider.\n\n - Deep familiarity with other strategic partner stacks: Platforms for AI workloads, network, and identity integration patterns. You know where Fireworks fits and where it doesn't.\n\n - Experience with agentic frameworks (LangChain, LlamaIndex, or custom tool-use pipelines) — you understand how inference latency and reliability shapes agent behavior at scale.\n\n - Background in model evaluation — you understand why benchmark gaming is rampant and what rigorous evals actually look like.\n\n - You've written a technical blog post or reference architecture that people actually read.\n\n - Track record taking GenAI POCs from prototype to production-scale deployments.\n\nOn-Target Expectations (Plus Equity)\n\n$200,000 - $260,000 USD\n\nTotal compensation also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"6746dfde-8f8d-4a13-9961-7ae1e222a4c0","title":"Member of Technical Staff","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"New York","secondaryLocations":[],"publishedAt":"2026-06-11T20:55:59.247+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"New York","addressCountry":"United States","addressLocality":"New York"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/6746dfde-8f8d-4a13-9961-7ae1e222a4c0","applyUrl":"https://jobs.ashbyhq.com/fireworks/6746dfde-8f8d-4a13-9961-7ae1e222a4c0/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
As a Training Infrastructure Engineer, you'll design, develop, and maintain large-scale backend and cloud-native infrastructure to support distributed machine learning training, inference, and data processing pipelines for our generative AI platform. You'll architect scalable, resilient backend infrastructure, lead technical design discussions, mentor engineers, and establish best practices for large-scale machine learning systems.
Architect and build scalable, resilient backend infrastructure to support distributed training, inference, and data processing pipelines
Lead technical design discussions, mentor engineers, and establish best practices for large-scale machine learning systems
Design and implement core backend services with a focus on efficiency and low latency
Drive infrastructure optimization initiatives for compute cost, storage lifecycle management, and network performance
Collaborate with machine learning, DevOps, and product teams to translate research and product requirements into robust infrastructure solutions
Evaluate and integrate cloud-native and open-source technologies such as Kubernetes, Ray, Kubeflow, and MLFlow to enhance platform reliability
Own end-to-end systems from design to deployment, emphasizing reliability, fault tolerance, and operational excellence
Bachelor's degree or equivalent in Computer Science or related field plus four (4) years of experience in software engineering or related role
4 years of experience designing, building, and optimizing large-scale backend infrastructure and distributed data systems (e.g., PostgreSQL, MySQL, DynamoDB, Apache Spark, Apache Flink, Apache Kafka) in cloud environments (AWS, GCP, Azure, or equivalent), including cloud-native platforms, core infrastructure components, and optimization techniques (caching, indexing, sharding, replication, transactions, ACID)
4 years of experience with major server-side programming languages and frameworks (e.g., Python, C++, Go, TypeScript)
4 years of experience writing technical design documentation, leading cross-functional projects, and collaborating with cross-functional teams to achieve business impact
3 years of experience developing and maintaining data processing and API systems, including client-server communication frameworks (e.g., gRPC, Thrift)
3 years of experience conducting A/B testing and scientific experimentation (e.g., Statsig, Meta Deltoid, Optimizely) to measure software impact
3 years of experience conducting coding interviews and providing systematic feedback for engineering candidates
2 years of experience with cloud-native tools and infrastructure, such as Docker and Kubernetes
2 years of experience defining and implementing data-driven metrics to support company or team goals
How to Apply: Submit resume and apply online at http://www.fireworks.ai/careers and search for job by title.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nAs a Training Infrastructure Engineer, you'll design, develop, and maintain large-scale backend and cloud-native infrastructure to support distributed machine learning training, inference, and data processing pipelines for our generative AI platform. You'll architect scalable, resilient backend infrastructure, lead technical design discussions, mentor engineers, and establish best practices for large-scale machine learning systems.\n\n\nKEY RESPONSIBILITIES:\n\n - Architect and build scalable, resilient backend infrastructure to support distributed training, inference, and data processing pipelines\n\n - Lead technical design discussions, mentor engineers, and establish best practices for large-scale machine learning systems\n\n - Design and implement core backend services with a focus on efficiency and low latency\n\n - Drive infrastructure optimization initiatives for compute cost, storage lifecycle management, and network performance\n\n - Collaborate with machine learning, DevOps, and product teams to translate research and product requirements into robust infrastructure solutions\n\n - Evaluate and integrate cloud-native and open-source technologies such as Kubernetes, Ray, Kubeflow, and MLFlow to enhance platform reliability\n\n - Own end-to-end systems from design to deployment, emphasizing reliability, fault tolerance, and operational excellence\n\n\nMINIMUM QUALIFICATIONS:\n\n - Bachelor's degree or equivalent in Computer Science or related field plus four (4) years of experience in software engineering or related role\n\n - 4 years of experience designing, building, and optimizing large-scale backend infrastructure and distributed data systems (e.g., PostgreSQL, MySQL, DynamoDB, Apache Spark, Apache Flink, Apache Kafka) in cloud environments (AWS, GCP, Azure, or equivalent), including cloud-native platforms, core infrastructure components, and optimization techniques (caching, indexing, sharding, replication, transactions, ACID)\n\n - 4 years of experience with major server-side programming languages and frameworks (e.g., Python, C++, Go, TypeScript)\n\n - 4 years of experience writing technical design documentation, leading cross-functional projects, and collaborating with cross-functional teams to achieve business impact\n\n - 3 years of experience developing and maintaining data processing and API systems, including client-server communication frameworks (e.g., gRPC, Thrift)\n\n - 3 years of experience conducting A/B testing and scientific experimentation (e.g., Statsig, Meta Deltoid, Optimizely) to measure software impact\n\n - 3 years of experience conducting coding interviews and providing systematic feedback for engineering candidates\n\n - 2 years of experience with cloud-native tools and infrastructure, such as Docker and Kubernetes\n\n - 2 years of experience defining and implementing data-driven metrics to support company or team goals\n\nHow to Apply: Submit resume and apply online at http://www.fireworks.ai/careers and search for job by title.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"7730b5a4-0b58-46c7-bcff-61a929a3d1bd","title":"AI Field Engineer - AI Natives","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-09T22:35:54.106+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/7730b5a4-0b58-46c7-bcff-61a929a3d1bd","applyUrl":"https://jobs.ashbyhq.com/fireworks/7730b5a4-0b58-46c7-bcff-61a929a3d1bd/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
AI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes.
You spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call.
The Segment
As a Field Engineer in the AI Native segment you will work with the most innovative AI-native companies building at the frontier, where GenAI is the core product, not a feature, and where Fireworks is the platform they depend on to ship and scale it. These engagements move fast with fewer stakeholders, so you will spend more time in the code and iterate alongside their engineering teams, while still holding executive-level conversations on architecture and strategy. You will embed deeply with a small set of high-velocity accounts where the quality of your engineering is the relationship.
What You'll Work On
Technical Delivery and Deployment
Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.
For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.
Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets
Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.
Model Strategy and Fine-Tuning
Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.
Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.
Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores.
Customer Engagement and Stakeholder Management
Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge.
Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.
Own the technical relationship from first engagement through production deployment. Embed with their engineering team as a peer, your credibility comes from what you build alongside them.
Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens.
Product Feedback and Platform Improvement
Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features.
Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself.
Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency.
Minimum Qualifications
5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.
Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.
Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).
Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.
Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.
Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.
Preferred Qualifications
10+ years in technical field or engineering roles.
Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.
Prior experience at a company with a forward-deployed or embedded engineering model (Palantir, Scale AI, Anthropic, OpenAI, BCG X, McKinsey Quantum Black, AI Native startups with FDE motions).
Prior experience as a technical founder or early engineer at an AI-native company is a strong signal.
Track record taking GenAI POCs from prototype to production-scale deployments.
Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex).
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nAI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes.\n\nYou spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call.\n\nThe Segment\n\nAs a Field Engineer in the AI Native segment you will work with the most innovative AI-native companies building at the frontier, where GenAI is the core product, not a feature, and where Fireworks is the platform they depend on to ship and scale it. These engagements move fast with fewer stakeholders, so you will spend more time in the code and iterate alongside their engineering teams, while still holding executive-level conversations on architecture and strategy. You will embed deeply with a small set of high-velocity accounts where the quality of your engineering is the relationship.\n\nWhat You'll Work On\n\nTechnical Delivery and Deployment\n\n - Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.\n\n - For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.\n\n - Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets\n\n - Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.\n\nModel Strategy and Fine-Tuning\n\n - Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.\n\n - Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.\n\n - Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores.\n\nCustomer Engagement and Stakeholder Management\n\n - Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge.\n\n - Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.\n\n - Own the technical relationship from first engagement through production deployment. Embed with their engineering team as a peer, your credibility comes from what you build alongside them.\n\n - Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens.\n\nProduct Feedback and Platform Improvement\n\n - Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features.\n\n - Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself.\n\n - Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency.\n\n\nWHAT WE'RE LOOKING FOR:\n\nMinimum Qualifications\n\n - 5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.\n\n - Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.\n\n - Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.\n\n - Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).\n\n - Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.\n\n - Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.\n\n - Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.\n\nPreferred Qualifications\n\n - 10+ years in technical field or engineering roles.\n\n - Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.\n\n - Prior experience at a company with a forward-deployed or embedded engineering model (Palantir, Scale AI, Anthropic, OpenAI, BCG X, McKinsey Quantum Black, AI Native startups with FDE motions).\n\n - Prior experience as a technical founder or early engineer at an AI-native company is a strong signal.\n\n - Track record taking GenAI POCs from prototype to production-scale deployments.\n\n - Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex).\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"69739e4f-1ca5-45db-8a70-4309d961c0b7","title":"AI Field Engineer - Enterprise","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-11T21:17:18.858+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/69739e4f-1ca5-45db-8a70-4309d961c0b7","applyUrl":"https://jobs.ashbyhq.com/fireworks/69739e4f-1ca5-45db-8a70-4309d961c0b7/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
The Role
AI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes.
You spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call.
The Segment
As a Field Engineer in the Enterprise track you will work with large organizations and digital-native companies adopting GenAI across the business. These engagements span more stakeholders and longer cycles, so you will manage executive relationships and align teams while staying hands-on in the code. The emphasis is on pairing strong technical delivery with the executive presence to earn trust across an org: discovery, solution design, POC execution, and the path to production at enterprise scale.
What You'll Work On
Technical Delivery and Deployment
Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.
For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.
Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets
Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.
Model Strategy and Fine-Tuning
Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.
Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.
Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores.
Customer Engagement and Stakeholder Management
Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge.
Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.
Own the technical relationship from first engagement through production deployment. Earn trust with ML engineers and VPs in the same meeting.
Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens.
Product Feedback and Platform Improvement
Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features.
Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself.
Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency.
What We're Looking For
Minimum Qualifications
5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.
Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.
Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).
Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.
Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.
Preferred Qualifications
10+ years in technical field or engineering roles.
Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.
Experience operating as a technical authority inside a customer's environment building within their infrastructure, navigating their constraints, and shipping code that runs in their production systems.
Track record taking GenAI POCs from prototype to production-scale deployments.
Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex).
Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\nThe Role\n\nAI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes.\n\nYou spend most of your time building. You ship code, run benchmarks, debug production issues, and architect deployments. But you also lead discovery conversations, align stakeholders, and translate customer pain points into product improvements that compress the feedback loop from field to roadmap. This is a role for engineers who are comfortable on-site with customers, building the relationships and trust that happen in person, not just over a call.\n\nThe Segment\n\nAs a Field Engineer in the Enterprise track you will work with large organizations and digital-native companies adopting GenAI across the business. These engagements span more stakeholders and longer cycles, so you will manage executive relationships and align teams while staying hands-on in the code. The emphasis is on pairing strong technical delivery with the executive presence to earn trust across an org: discovery, solution design, POC execution, and the path to production at enterprise scale.\n\nWhat You'll Work On\n\nTechnical Delivery and Deployment\n\n - Build end-to-end POCs and MVPs alongside customer engineering teams, working inside their codebases, infrastructure, and constraints.\n\n - For customers whose core product is built on GenAI, architect the inference foundations that capability depends on, and size deployments so they can scale in their market without infrastructure becoming the bottleneck.\n\n - Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles, and tune deployments to hit those targets\n\n - Deploy and validate new model families on inference frameworks (vLLM, SGLang), determining optimal shapes, quantization configs, and serving patterns across workloads.\n\nModel Strategy and Fine-Tuning\n\n - Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology.\n\n - Build and run fine-tuning pipelines directly with customers, navigating trade-offs between model families, compute cost, and quality targets.\n\n - Design and implement evaluation frameworks that measure production-quality metrics, not just benchmark scores.\n\nCustomer Engagement and Stakeholder Management\n\n - Many of our customers exist because of GenAI. Help them bake frontier model capabilities into their core offering and turn that into a durable competitive edge.\n\n - Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions.\n\n - Own the technical relationship from first engagement through production deployment. Earn trust with ML engineers and VPs in the same meeting.\n\n - Spend time on-site with customers. Build trust and momentum in person, embedding with their teams where the work happens.\n\nProduct Feedback and Platform Improvement\n\n - Identify recurring customer pain points and translate them into concrete product proposals, working directly with engineering and product to ship fixes and features.\n\n - Codify repeatable deployment patterns and contribute them back to internal tooling, documentation, and the platform itself.\n\n - Feed customer signals (deployment patterns, failure modes, feature gaps) back into the product roadmap with specificity and urgency.\n\nWhat We're Looking For\n\nMinimum Qualifications\n\n - 5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.\n\n - Demonstrated ability to build production software with customers, not just advise on it. You have shipped code running in someone else's production environment.\n\n - Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.\n\n - Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus).\n\n - Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.\n\n - Exceptional communication: able to run a sharp discovery call, present to a VP, and debug a latency issue with an ML engineer in the same afternoon.\n\nPreferred Qualifications\n\n - 10+ years in technical field or engineering roles.\n\n - Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and tuning deployments for real workloads.\n\n - Experience operating as a technical authority inside a customer's environment building within their infrastructure, navigating their constraints, and shipping code that runs in their production systems.\n\n - Track record taking GenAI POCs from prototype to production-scale deployments.\n\n - Experience with hyperscaler AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex).\n\n - Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"b8d56b42-0eea-4480-b5a9-df74d46d5987","title":"Head of Systems Integrators","department":"Go To Market","team":"Partnerships","employmentType":"FullTime","location":"Remote","secondaryLocations":[],"publishedAt":"2026-06-20T01:56:39.962+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/fireworks/b8d56b42-0eea-4480-b5a9-df74d46d5987","applyUrl":"https://jobs.ashbyhq.com/fireworks/b8d56b42-0eea-4480-b5a9-df74d46d5987/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
SIs are Fireworks' highest-leverage GTM channel and this function does not exist yet. The person in this role originates and structures the deals, builds the partners, makes them technically capable, and embeds Fireworks into how they sell. The weight is upstream: strategy and origination, not day-to-day partner management.
Originate and Structure
Source and close first-of-a-kind commercial agreements with Tier-1 SIs - framework deals, global MoUs, joint offering structures - where no playbook exists
Define the multi-practice value proposition; align SI executive and line-of-business leadership on why Fireworks and how joint delivery creates margin for both sides
Navigate matrixed GSI org structures to secure internal mandates for dedicated practices or CoEs, aligning competing service lines on governance and delivery standards
Define co-delivery swimlanes and market ownership to prevent channel conflict and protect delivery quality as the partner ecosystem scales
Recruit and Develop
Identify and recruit Tier-1 SI partners with credible AI practices, client access in target verticals, and appetite to build a Fireworks capability
Build conviction at every level - make the commercial and technical case from alliance desk to equity partner
Connect Fireworks engineers, sales, and product to their counterparts at the partner; establish functional working relationships, not just an alliance desk
Guide partners through standing up a Fireworks service offering: capability definition, staffing model, pricing, and GTM positioning
Enable
Design and own FDE certification: inference, fine-tuning pipelines, production deployment - with a track covering SFT, RLHF, and model adaptation
Build the operating model: how projects flow to partners, support tiers, escalation to the Fireworks technical bench, and commercial attribution
Run the direct interface desk - standing technical bridge between partner delivery teams and Fireworks engineers for in-flight engagements
Own model update continuity: when Fireworks ships, re-certify partners before delivery is disrupted
Embed
Place Fireworks in SI practice playbooks and internal solution frameworks - the default inference layer when their AI practices architect for clients
Produce joint innovation content with named Fireworks placement: reference architectures, solution briefs, and thought leadership under partner credentials
Develop case studies with specific, attributable outcomes - latency, cost reduction, model quality - with named clients where possible
Build at practice lead and delivery principal level across all active SI partners, not just alliance managers
What matters is that you are a practitioner - close enough to how SIs work to know where the leverage is and where the friction lives.
You are technical enough to earn credibility with FDEs and ML engineers - you understand what SFT and RL mean in production and can design enablement that builds those capabilities in others. GSI experience is a strong plus, not a requirement. What is required: you have closed non-standard strategic agreements before, and you build things that do not exist yet.
8-10 years across top-tier consulting, enterprise technology or AI/ML vendor roles, or senior SI alliance leadership - with direct exposure to how GSIs structure, sell, and deliver
Track record closing non-standard strategic agreements: MoUs, framework deals, joint offering structures with major GSIs or consulting firms
Working knowledge of how GSIs operate - practice formation, CoE funding, delivery authority, internal service line competition - from the inside or from working alongside them closely
ML stack fluency sufficient to design and assess technical enablement: fine-tuning, inference, deployment pipelines
Demonstrated 0-to-1 program or function builds; not inherited playbooks
Operates at C-suite and equity partner level; measures success by pipeline originated and practice maturity, not activity
Bonus:
Time inside the AI practice of a leading GSI or MBB firm
Hands-on post-training experience: SFT, RL, or RLHF in delivery or program management
Existing relationships at practice lead or delivery principal level within major consulting or SI AI practices
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nSIs are Fireworks' highest-leverage GTM channel and this function does not exist yet. The person in this role originates and structures the deals, builds the partners, makes them technically capable, and embeds Fireworks into how they sell. The weight is upstream: strategy and origination, not day-to-day partner management.\n\n\nWHAT YOU WILL OWN: \n\nOriginate and Structure\n\n - Source and close first-of-a-kind commercial agreements with Tier-1 SIs - framework deals, global MoUs, joint offering structures - where no playbook exists\n\n - Define the multi-practice value proposition; align SI executive and line-of-business leadership on why Fireworks and how joint delivery creates margin for both sides\n\n - Navigate matrixed GSI org structures to secure internal mandates for dedicated practices or CoEs, aligning competing service lines on governance and delivery standards\n\n - Define co-delivery swimlanes and market ownership to prevent channel conflict and protect delivery quality as the partner ecosystem scales\n\nRecruit and Develop\n\n - Identify and recruit Tier-1 SI partners with credible AI practices, client access in target verticals, and appetite to build a Fireworks capability\n\n - Build conviction at every level - make the commercial and technical case from alliance desk to equity partner\n\n - Connect Fireworks engineers, sales, and product to their counterparts at the partner; establish functional working relationships, not just an alliance desk\n\n - Guide partners through standing up a Fireworks service offering: capability definition, staffing model, pricing, and GTM positioning\n\nEnable\n\n - Design and own FDE certification: inference, fine-tuning pipelines, production deployment - with a track covering SFT, RLHF, and model adaptation\n\n - Build the operating model: how projects flow to partners, support tiers, escalation to the Fireworks technical bench, and commercial attribution\n\n - Run the direct interface desk - standing technical bridge between partner delivery teams and Fireworks engineers for in-flight engagements\n\n - Own model update continuity: when Fireworks ships, re-certify partners before delivery is disrupted\n\nEmbed\n\n - Place Fireworks in SI practice playbooks and internal solution frameworks - the default inference layer when their AI practices architect for clients\n\n - Produce joint innovation content with named Fireworks placement: reference architectures, solution briefs, and thought leadership under partner credentials\n\n - Develop case studies with specific, attributable outcomes - latency, cost reduction, model quality - with named clients where possible\n\n - Build at practice lead and delivery principal level across all active SI partners, not just alliance managers\n\n\nWHO YOU ARE: \n\nWhat matters is that you are a practitioner - close enough to how SIs work to know where the leverage is and where the friction lives. \n\nYou are technical enough to earn credibility with FDEs and ML engineers - you understand what SFT and RL mean in production and can design enablement that builds those capabilities in others. GSI experience is a strong plus, not a requirement. What is required: you have closed non-standard strategic agreements before, and you build things that do not exist yet.\n\n\nWHAT YOU BRING:\n\n - 8-10 years across top-tier consulting, enterprise technology or AI/ML vendor roles, or senior SI alliance leadership - with direct exposure to how GSIs structure, sell, and deliver\n\n - Track record closing non-standard strategic agreements: MoUs, framework deals, joint offering structures with major GSIs or consulting firms\n\n - Working knowledge of how GSIs operate - practice formation, CoE funding, delivery authority, internal service line competition - from the inside or from working alongside them closely\n\n - ML stack fluency sufficient to design and assess technical enablement: fine-tuning, inference, deployment pipelines\n\n - Demonstrated 0-to-1 program or function builds; not inherited playbooks\n\n - Operates at C-suite and equity partner level; measures success by pipeline originated and practice maturity, not activity\n\nBonus: \n\n - Time inside the AI practice of a leading GSI or MBB firm\n\n - Hands-on post-training experience: SFT, RL, or RLHF in delivery or program management\n\n - Existing relationships at practice lead or delivery principal level within major consulting or SI AI practices\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"9845269e-114b-4755-86d5-b7181ba58663","title":"AWS Partner Development Manager","department":"Go To Market","team":"Partnerships","employmentType":"FullTime","location":"Remote","secondaryLocations":[],"publishedAt":"2026-06-22T17:02:06.649+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/fireworks/9845269e-114b-4755-86d5-b7181ba58663","applyUrl":"https://jobs.ashbyhq.com/fireworks/9845269e-114b-4755-86d5-b7181ba58663/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
Fireworks AI has an established AWS partnership and is now building the field motion that converts it into enterprise revenue. This role owns that execution: co-sell pipeline, partner events, and the joint GTM programs that earn Fireworks AI a seat in AWS field deals before they are already decided. The weight sits on origination - getting in front of the right account teams, building trust, and creating the conditions for large deals to move.
Source and Close Co-Sell Pipeline
Run joint account mapping with AWS PDMs to surface Fireworks-adjacent workloads in active enterprise accounts.
Register co-sell opportunities in ACE; own each from qualification to close working alongside Fireworks AEs.
Lead high-touch engagement on priority accounts: joint calls, on-sites, and executive introductions with AWS field sellers.
Track pipeline velocity and AWS-influenced revenue; flag stalled deals to VP with a clear recommended action.
Partner Events and Follow-Up
Own Fireworks AI presence at AWS Summits, re:Invent, and regional field events: meeting strategy, priorities, and speaker submissions.
Build pre-event target lists with AWS PDMs and execute outreach in the 4 weeks before each event.
Convert post-event meetings to ACE registrations and AE handoffs within 5 business days - no leads left to go cold.
Track event-sourced pipeline per activation; report attribution to VP and feed results into future event planning.
Build the AWS GTM Motion
Author joint solution briefs targeting enterprise AI inference use cases on AWS; get AWS SA sign-off before publishing.
Develop co-sell plays for key verticals - financial services, healthcare, tech - mapped to specific AWS SA coverage.
Build Fireworks AI presence in Bedrock and SageMaker-adjacent workflows through co-built reference architectures.
Coordinate with Fireworks marketing on AWS-specific demand generation and co-marketing assets.
Operationalize and Measure
Own Fireworks AI AWS Marketplace metrics: trial conversions, CPPO transactions, and revenue attribution.
Maintain a shared pipeline dashboard visible to both Fireworks and AWS stakeholders; review at each QBR.
Identify and submit MAP and co-invest funding proposals; manage them through to approval and execution.
Surface blockers in product positioning, tier standing, or program gaps to VP with proposed fixes.
Maintain and Grow the Relationship
Run quarterly business reviews with AWS PDMs and leadership; arrive with pipeline data, win stories, and next-quarter commitments.
Expand Fireworks AI contacts beyond the primary PDM: AWS SAs, ISV team leadership, and Marketplace team.
Track changes in AWS program terms, co-sell incentives, and tier requirements; adapt Fireworks positioning ahead of the curve.
Maintain an internal AWS relationship map - contacts, roles, last meaningful interaction - updated each quarter.
You have sourced real pipeline from the AWS field - self-generated, not handed to you. AWS AEs and PDMs in multiple regions know your name because you have worked deals with them, and they would take your call today. You have closed large enterprise deals through the AWS co-sell channel and can walk through how those deals moved - who the account team was, what unlocked them, and what you did when they stalled.
You have sold technical products to technical buyers. You are comfortable in a room with AWS Solutions Architects or a customer VP of Engineering without a pre-sales resource next to you. You know the AWS partner programs well enough that you do not need to be briefed on how ACE, ISV Accelerate, or Marketplace work. You are comfortable stepping into an existing motion and making it faster, not starting from zero.
6-8 years in cloud partnerships, ISV alliances, or field sales with AWS as the primary motion - not one of several cloud relationships.
Closed large enterprise deals through the AWS co-sell channel with verifiable named accounts; deal size and complexity consistent with strategic enterprise AI.
Deep working knowledge of APN programs, ISV Accelerate co-sell terms, AWS Marketplace and CPPO, and ACE pipeline tooling.
Has sold a technically complex product and can engage with AWS SAs and technical buyers without needing a pre-sales translator.
Has planned, staffed, and followed up from major AWS field events - Summit, re:Invent - and can show the pipeline that came from them.
Bonus
Has a pre-existing network inside AWS enterprise and startup-focused sales teams in key US markets - contacts ready to engage on day one.
Has experience navigating an AWS co-sell motion where the product was newer and less established - had to earn credibility, not ride existing demand.
Has been part of a joint AWS solution that got featured in an AWS case study, Marketplace listing, or field playbook.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE\n\nFireworks AI has an established AWS partnership and is now building the field motion that converts it into enterprise revenue. This role owns that execution: co-sell pipeline, partner events, and the joint GTM programs that earn Fireworks AI a seat in AWS field deals before they are already decided. The weight sits on origination - getting in front of the right account teams, building trust, and creating the conditions for large deals to move.\n\n\nWHAT YOU'LL OWN\n\nSource and Close Co-Sell Pipeline\n\n - Run joint account mapping with AWS PDMs to surface Fireworks-adjacent workloads in active enterprise accounts.\n\n - Register co-sell opportunities in ACE; own each from qualification to close working alongside Fireworks AEs.\n\n - Lead high-touch engagement on priority accounts: joint calls, on-sites, and executive introductions with AWS field sellers.\n\n - Track pipeline velocity and AWS-influenced revenue; flag stalled deals to VP with a clear recommended action.\n\nPartner Events and Follow-Up\n\n - Own Fireworks AI presence at AWS Summits, re:Invent, and regional field events: meeting strategy, priorities, and speaker submissions.\n\n - Build pre-event target lists with AWS PDMs and execute outreach in the 4 weeks before each event.\n\n - Convert post-event meetings to ACE registrations and AE handoffs within 5 business days - no leads left to go cold.\n\n - Track event-sourced pipeline per activation; report attribution to VP and feed results into future event planning.\n\nBuild the AWS GTM Motion\n\n - Author joint solution briefs targeting enterprise AI inference use cases on AWS; get AWS SA sign-off before publishing.\n\n - Develop co-sell plays for key verticals - financial services, healthcare, tech - mapped to specific AWS SA coverage.\n\n - Build Fireworks AI presence in Bedrock and SageMaker-adjacent workflows through co-built reference architectures.\n\n - Coordinate with Fireworks marketing on AWS-specific demand generation and co-marketing assets.\n\nOperationalize and Measure\n\n - Own Fireworks AI AWS Marketplace metrics: trial conversions, CPPO transactions, and revenue attribution.\n\n - Maintain a shared pipeline dashboard visible to both Fireworks and AWS stakeholders; review at each QBR.\n\n - Identify and submit MAP and co-invest funding proposals; manage them through to approval and execution.\n\n - Surface blockers in product positioning, tier standing, or program gaps to VP with proposed fixes.\n\nMaintain and Grow the Relationship\n\n - Run quarterly business reviews with AWS PDMs and leadership; arrive with pipeline data, win stories, and next-quarter commitments.\n\n - Expand Fireworks AI contacts beyond the primary PDM: AWS SAs, ISV team leadership, and Marketplace team.\n\n - Track changes in AWS program terms, co-sell incentives, and tier requirements; adapt Fireworks positioning ahead of the curve.\n\n - Maintain an internal AWS relationship map - contacts, roles, last meaningful interaction - updated each quarter.\n\n\nWHO YOU ARE\n\nYou have sourced real pipeline from the AWS field - self-generated, not handed to you. AWS AEs and PDMs in multiple regions know your name because you have worked deals with them, and they would take your call today. You have closed large enterprise deals through the AWS co-sell channel and can walk through how those deals moved - who the account team was, what unlocked them, and what you did when they stalled.\n\nYou have sold technical products to technical buyers. You are comfortable in a room with AWS Solutions Architects or a customer VP of Engineering without a pre-sales resource next to you. You know the AWS partner programs well enough that you do not need to be briefed on how ACE, ISV Accelerate, or Marketplace work. You are comfortable stepping into an existing motion and making it faster, not starting from zero.\n\n\nWHAT YOU BRING\n\n - 6-8 years in cloud partnerships, ISV alliances, or field sales with AWS as the primary motion - not one of several cloud relationships.\n\n - Closed large enterprise deals through the AWS co-sell channel with verifiable named accounts; deal size and complexity consistent with strategic enterprise AI.\n\n - Deep working knowledge of APN programs, ISV Accelerate co-sell terms, AWS Marketplace and CPPO, and ACE pipeline tooling.\n\n - Has sold a technically complex product and can engage with AWS SAs and technical buyers without needing a pre-sales translator.\n\n - Has planned, staffed, and followed up from major AWS field events - Summit, re:Invent - and can show the pipeline that came from them.\n\nBonus\n\n - Has a pre-existing network inside AWS enterprise and startup-focused sales teams in key US markets - contacts ready to engage on day one.\n\n - Has experience navigating an AWS co-sell motion where the product was newer and less established - had to earn credibility, not ride existing demand.\n\n - Has been part of a joint AWS solution that got featured in an AWS case study, Marketplace listing, or field playbook.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"da8f0b05-ac82-40a4-8cb8-64767c956018","title":"Social and Community Manager ","department":"Marketing","team":"Marketing","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-26T18:44:08.701+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/da8f0b05-ac82-40a4-8cb8-64767c956018","applyUrl":"https://jobs.ashbyhq.com/fireworks/da8f0b05-ac82-40a4-8cb8-64767c956018/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
The AI infrastructure industry moves faster than almost anything in tech. New models, benchmarks, and techniques land weekly, and the narrative around them forms in days or hours. We're hiring a Social and Community Manager who can read those waves, ride the ones worth riding, add signal to them, and start narratives of our own that catch and spread.
This is a hands-on, execution-heavy role with judgment at its core. You'll decide what's worth reacting to, what we should say, and when. You'll back those calls with data, ship consistently across our social and community channels, and support marketing and product by turning a fast-moving field into content people actually want to share.
Narrative & Trend Judgment
Track conversations relevant to Fireworks in real time, judge what's worth jumping on versus noise, and move fast when a moment opens with a strong instinct for tone and timing. Frame narratives that give the community and market a reason to talk about Fireworks, not just one-off posts.
Data, Analysis & Reporting
Monitor social, Discord, and community platforms daily using analytics tools. Track the metrics that matter (engagement, reach, sentiment, growth, community health), turn them into clear reports, and use insights to recommend content changes, experiments, and next steps.
Content Creation & Execution
Create on-brand content informed by data, trends, and community feedback. Generate fresh formats that make technical AI topics shareable, own the social calendar, and ship consistently without losing the creative edge.
Community Engagement
Moderate discussions, answer questions, welcome members, and foster helpful conversations. Support and help run community programs (Champion/Ambassador initiatives, newsletters, AMAs, cohorts), and proactively spot ways to strengthen connections.
Events & Cross-Team Collaboration
Help plan and execute virtual and in-person events, webinars, and meetups, measuring impact to improve future ones. Keep calendars, trackers, and dashboards meticulously organized, and share data-driven insights with marketing, product, and engineering so efforts run smoothly and scale.
Must-Haves
3–6 years of hands-on experience in social media management or community management (developer or AI communities preferred).
Sharp judgment on what's worth a reaction and what to ignore, plus a track record of content or narratives that actually traveled.
Strong excellence in data and analytics, you confidently track metrics, interpret performance, create reports/dashboards, and use insights to guide execution and optimization.
Self-starter mindset: comfortable proactively identifying trends and opportunities, then recommending actions or ideas to the team.
Creative thinker who generates fresh content ideas and approaches while staying on-brand.
Hands-on experience actively engaging and growing communities (Discord, Reddit, X, forums, etc.).
Experience with social and community analytics tools (native platforms + tools like Sprout Social or similar).
Meticulously organized with strong project management skills.
AI native, you use LLMs and generative AI tools daily and understand developer workflows around models and inference.
Strong execution skills: reliable, detail-oriented, and proactive in delivering high-quality work in a fast-paced environment.
Nice-to-Haves
Experience supporting or contributing to community programs and events.
Familiarity with AI infrastructure or open-source model communities (e.g., Hugging Face ecosystem).
Basic video or multimedia production skills.
Background in fast-paced startup environments
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE\n\nThe AI infrastructure industry moves faster than almost anything in tech. New models, benchmarks, and techniques land weekly, and the narrative around them forms in days or hours. We're hiring a Social and Community Manager who can read those waves, ride the ones worth riding, add signal to them, and start narratives of our own that catch and spread.\n\nThis is a hands-on, execution-heavy role with judgment at its core. You'll decide what's worth reacting to, what we should say, and when. You'll back those calls with data, ship consistently across our social and community channels, and support marketing and product by turning a fast-moving field into content people actually want to share.\n\n\nKEY RESPONSIBILITIES\n\nNarrative & Trend Judgment \n\nTrack conversations relevant to Fireworks in real time, judge what's worth jumping on versus noise, and move fast when a moment opens with a strong instinct for tone and timing. Frame narratives that give the community and market a reason to talk about Fireworks, not just one-off posts.\n\nData, Analysis & Reporting\n\nMonitor social, Discord, and community platforms daily using analytics tools. Track the metrics that matter (engagement, reach, sentiment, growth, community health), turn them into clear reports, and use insights to recommend content changes, experiments, and next steps.\n\nContent Creation & Execution \n\nCreate on-brand content informed by data, trends, and community feedback. Generate fresh formats that make technical AI topics shareable, own the social calendar, and ship consistently without losing the creative edge.\n\nCommunity Engagement \n\nModerate discussions, answer questions, welcome members, and foster helpful conversations. Support and help run community programs (Champion/Ambassador initiatives, newsletters, AMAs, cohorts), and proactively spot ways to strengthen connections.\n\nEvents & Cross-Team Collaboration \n\nHelp plan and execute virtual and in-person events, webinars, and meetups, measuring impact to improve future ones. Keep calendars, trackers, and dashboards meticulously organized, and share data-driven insights with marketing, product, and engineering so efforts run smoothly and scale.\n\n\nWHAT WE’RE LOOKING FOR\n\nMust-Haves\n\n - 3–6 years of hands-on experience in social media management or community management (developer or AI communities preferred).\n\n - Sharp judgment on what's worth a reaction and what to ignore, plus a track record of content or narratives that actually traveled.\n\n - Strong excellence in data and analytics, you confidently track metrics, interpret performance, create reports/dashboards, and use insights to guide execution and optimization.\n\n - Self-starter mindset: comfortable proactively identifying trends and opportunities, then recommending actions or ideas to the team.\n\n - Creative thinker who generates fresh content ideas and approaches while staying on-brand.\n\n - Hands-on experience actively engaging and growing communities (Discord, Reddit, X, forums, etc.).\n\n - Experience with social and community analytics tools (native platforms + tools like Sprout Social or similar).\n\n - Meticulously organized with strong project management skills.\n\n - AI native, you use LLMs and generative AI tools daily and understand developer workflows around models and inference.\n\n - Strong execution skills: reliable, detail-oriented, and proactive in delivering high-quality work in a fast-paced environment.\n\n\nNice-to-Haves\n\n - Experience supporting or contributing to community programs and events.\n\n - Familiarity with AI infrastructure or open-source model communities (e.g., Hugging Face ecosystem).\n\n - Basic video or multimedia production skills.\n\n - Background in fast-paced startup environments\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"e4b18de8-aaf4-4acc-b1f6-9182d23e942c","title":"Brand Design Lead","department":"Marketing","team":"Marketing","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-29T23:45:12.403+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/e4b18de8-aaf4-4acc-b1f6-9182d23e942c","applyUrl":"https://jobs.ashbyhq.com/fireworks/e4b18de8-aaf4-4acc-b1f6-9182d23e942c/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
The brand story at Fireworks is still being written, and this is the role that owns it. You’ll report to the Head of Brand and Web, taking end-to-end responsibility for how Fireworks shows up visually: from collaborating on a full brand refresh with an external agency, to defining the system that carries it forward, to building the team that scales it.
Work directly with the Head of Brand and our agency partner on the brand refresh, representing the internal creative voice, pressure-testing decisions, and ensuring the work translates into something we can actually build on
Help define and codify the brand as it takes shape: visual identity, tone, design language, and the rules that hold it together
Build and maintain a design system that is well documented, practical, and actually used across the company
Build self-serve design resources and workflows that enable the wider team to move independently on day-to-day needs, including templates, brand-compliant tooling in Canva, and AI-powered design tools, so senior design time is spent where it matters most
Own the visual execution across brand surfaces: web, social, events, sales collateral, and whatever else the company needs
Concept and execute brand campaigns across digital and out-of-home, from paid social and display to large-format outdoor, ensuring the work is consistent, distinctive, and built to perform in market
Able to move quickly without sacrificing quality
6+ years of brand design experience building brands for technically complex products. AI, developer tools, or enterprise infrastructure. You know what it takes to make something deeply technical feel compelling and clear
Strong portfolio spanning brand identity, design systems, and web design, ideally in B2B or developer-facing products
Experience working with or alongside external agency partners, with a track record of getting the most out of that relationship
Someone who takes ownership seriously: you drive things to completion, raise the quality bar, and build the structures that let others do the same
Figma as second nature. Bonus if you have enough web sensibility to work closely with engineers (light HTML/CSS, Webflow, or similar)
Proven ability to operate in ambiguity. You don’t need a finished brief to start making good decisions
Has opinions. Backs them up. Takes feedback well.
We’re working with an external agency on a full brand overhaul. This role isn’t responsible for owning or directing that engagement, but you’ll be a key collaborator inside it, with high exposure, real creative input, and the opportunity to shape what we take forward. You need to be comfortable with ambiguity and good at making progress while things are still being figured out.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE\n\nThe brand story at Fireworks is still being written, and this is the role that owns it. You’ll report to the Head of Brand and Web, taking end-to-end responsibility for how Fireworks shows up visually: from collaborating on a full brand refresh with an external agency, to defining the system that carries it forward, to building the team that scales it.\n\n\nWHAT YOU'LL DO\n\n - Work directly with the Head of Brand and our agency partner on the brand refresh, representing the internal creative voice, pressure-testing decisions, and ensuring the work translates into something we can actually build on\n\n - Help define and codify the brand as it takes shape: visual identity, tone, design language, and the rules that hold it together\n\n - Build and maintain a design system that is well documented, practical, and actually used across the company\n\n - Build self-serve design resources and workflows that enable the wider team to move independently on day-to-day needs, including templates, brand-compliant tooling in Canva, and AI-powered design tools, so senior design time is spent where it matters most\n\n - Own the visual execution across brand surfaces: web, social, events, sales collateral, and whatever else the company needs\n\n - Concept and execute brand campaigns across digital and out-of-home, from paid social and display to large-format outdoor, ensuring the work is consistent, distinctive, and built to perform in market\n\n - Able to move quickly without sacrificing quality\n\n\nWHAT WE'RE LOOKING FOR\n\n - 6+ years of brand design experience building brands for technically complex products. AI, developer tools, or enterprise infrastructure. You know what it takes to make something deeply technical feel compelling and clear\n\n - Strong portfolio spanning brand identity, design systems, and web design, ideally in B2B or developer-facing products\n\n - Experience working with or alongside external agency partners, with a track record of getting the most out of that relationship\n\n - Someone who takes ownership seriously: you drive things to completion, raise the quality bar, and build the structures that let others do the same\n\n - Figma as second nature. Bonus if you have enough web sensibility to work closely with engineers (light HTML/CSS, Webflow, or similar)\n\n - Proven ability to operate in ambiguity. You don’t need a finished brief to start making good decisions\n\n - Has opinions. Backs them up. Takes feedback well.\n\n\nA NOTE ON THE AGENCY REDESIGN\n\nWe’re working with an external agency on a full brand overhaul. This role isn’t responsible for owning or directing that engagement, but you’ll be a key collaborator inside it, with high exposure, real creative input, and the opportunity to shape what we take forward. You need to be comfortable with ambiguity and good at making progress while things are still being figured out.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"88570452-262e-4738-b36d-9ff9229f543f","title":"Web Marketing & Operations Lead","department":"Marketing","team":"Marketing","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-06-29T23:44:51.271+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/88570452-262e-4738-b36d-9ff9229f543f","applyUrl":"https://jobs.ashbyhq.com/fireworks/88570452-262e-4738-b36d-9ff9229f543f/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
This is a founding role. You will be the first engineering hire on the marketing team at Fireworks AI: the person who owns the web platform end-to-end, and who brings the technical credibility to everything marketing builds online.
The immediate priority is a significant web refresh. We already have an established platform: a Next.js monorepo (Turborepo + Yarn workspaces) with Sanity as our content source of truth, deployed on Vercel with ISR. The goal is to improve, scale, and mature that platform rather than rebuild it. You will work alongside a strong agency partner who brings deep technical and strategic expertise — rather than being heads-down in execution, your focus will be on technical leadership, platform direction, and ensuring the work meets a high bar.
This is a senior IC role. You will be embedded with the marketing team, partnering closely with Marketing Operations, Digital, and Growth, and working cross-functionally with product and engineering. You are directly accountable for the quality and performance of our web presence as the company scales at pace.
Own the architecture and health of the Fireworks marketing web platform: a Next.js 15 monorepo with shared component libraries, Sanity Studio, and Vercel hosting.
Evolve and scale the existing Sanity content architecture, improving content modelling, GROQ queries, and dataset structure to give marketing, digital, and growth teams greater independence.
Lead the technical execution of the web refresh, setting direction, defining milestones, and keeping the project on track without a dedicated PM.
Work alongside the agency partner on technical strategy and delivery, reviewing output, translating briefs, and holding work to a high standard.
Manage Vercel deployment workflows, ISR revalidation, preview environments, and third-party integrations including Mux, HubSpot, and GitHub Actions pipelines.
Drive performance best practices across Core Web Vitals, Lighthouse, caching, accessibility (WCAG), and SEO.
Partner with Marketing Operations on martech integrations and tooling, and collaborate with Digital and Growth on experimentation, landing pages, and analytics.
Communicate progress, decisions, and trade-offs clearly to non-technical stakeholders and leadership.
Next.js 15 (React) with TypeScript, monorepo via Turborepo + Yarn workspaces Framework:
Sanity Studio v3, GROQ queries via groqd, production and staging datasets CMS:
Vercel with ISR and on-demand revalidation Hosting & Deployment:
Mux Video:
HubSpot CRM / Forms:
GitHub Actions Pipelines:
external agency Execution partner:
Required
6-8+ years of professional experience in full-stack or frontend-heavy web development.
4+ years of production experience with React and Next.js, including SSR, SSG, app router, and performance optimisation.
Strong fluency in TypeScript and modern JavaScript (ES6+).
Deep experience with Sanity or a comparable headless CMS, including content modelling, GROQ, structured data, and composable architecture.
Proficiency with Vercel: deployments, ISR, edge functions, preview environments, and environment management.
Solid grasp of Core Web Vitals, Lighthouse performance auditing, and frontend performance tuning.
Familiarity with CI/CD pipelines and GitHub Actions.
Experience managing third-party integrations (video hosting, CRM, marketing tooling).
Proven ability to manage an external agency or vendor: directing, reviewing, and holding partners accountable.
Strong project management instincts: you can own delivery end-to-end without a dedicated PM.
Clear, direct communicator, equally comfortable writing a technical spec and presenting trade-offs to marketing leadership.
Comfortable operating autonomously in a small, fast-moving environment where priorities shift and pace is relentless.
Nice to Have
Experience improving and scaling an existing web platform, ideally on a headless CMS and Jamstack stack.
Familiarity with marketing analytics platforms: GA4, Segment, PostHog, Adobe Analytics, or similar.
Hands-on experience with HubSpot integrations or similar CRM/marketing automation tooling.
Experience with automated testing frameworks (Jest, Cypress, Playwright).
Familiarity with monorepo tooling such as Turborepo or Nx.
Familiarity with AI or developer-tooling products (bonus for Fireworks-adjacent domain knowledge).
Experience in a founding or first-in-function role at a startup or scale-up.
Who Thrives Here
You are energised by ownership, not overwhelmed by it. You are comfortable being the only engineer in the room, confident making calls, and able to clearly articulate why. You bridge technical depth with business outcomes and you know how to design systems that unlock collaboration between content, design, and development. You care about craft but know when to move fast.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nABOUT THE ROLE\n\nThis is a founding role. You will be the first engineering hire on the marketing team at Fireworks AI: the person who owns the web platform end-to-end, and who brings the technical credibility to everything marketing builds online.\n\nThe immediate priority is a significant web refresh. We already have an established platform: a Next.js monorepo (Turborepo + Yarn workspaces) with Sanity as our content source of truth, deployed on Vercel with ISR. The goal is to improve, scale, and mature that platform rather than rebuild it. You will work alongside a strong agency partner who brings deep technical and strategic expertise — rather than being heads-down in execution, your focus will be on technical leadership, platform direction, and ensuring the work meets a high bar.\n\nThis is a senior IC role. You will be embedded with the marketing team, partnering closely with Marketing Operations, Digital, and Growth, and working cross-functionally with product and engineering. You are directly accountable for the quality and performance of our web presence as the company scales at pace.\n\n\nWHAT YOU’LL DO\n\n - Own the architecture and health of the Fireworks marketing web platform: a Next.js 15 monorepo with shared component libraries, Sanity Studio, and Vercel hosting.\n\n - Evolve and scale the existing Sanity content architecture, improving content modelling, GROQ queries, and dataset structure to give marketing, digital, and growth teams greater independence.\n\n - Lead the technical execution of the web refresh, setting direction, defining milestones, and keeping the project on track without a dedicated PM.\n\n - Work alongside the agency partner on technical strategy and delivery, reviewing output, translating briefs, and holding work to a high standard.\n\n - Manage Vercel deployment workflows, ISR revalidation, preview environments, and third-party integrations including Mux, HubSpot, and GitHub Actions pipelines.\n\n - Drive performance best practices across Core Web Vitals, Lighthouse, caching, accessibility (WCAG), and SEO.\n\n - Partner with Marketing Operations on martech integrations and tooling, and collaborate with Digital and Growth on experimentation, landing pages, and analytics.\n\n - Communicate progress, decisions, and trade-offs clearly to non-technical stakeholders and leadership.\n\n\nTHE STACK\n\n - Next.js 15 (React) with TypeScript, monorepo via Turborepo + Yarn workspaces Framework:\n\n - Sanity Studio v3, GROQ queries via groqd, production and staging datasets CMS:\n\n - Vercel with ISR and on-demand revalidation Hosting & Deployment:\n\n - Mux Video:\n\n - HubSpot CRM / Forms:\n\n - GitHub Actions Pipelines:\n\n - external agency Execution partner:\n\n\nWHAT WE’RE LOOKING FOR\n\nRequired\n\n - 6-8+ years of professional experience in full-stack or frontend-heavy web development.\n\n - 4+ years of production experience with React and Next.js, including SSR, SSG, app router, and performance optimisation.\n\n - Strong fluency in TypeScript and modern JavaScript (ES6+).\n\n - Deep experience with Sanity or a comparable headless CMS, including content modelling, GROQ, structured data, and composable architecture.\n\n - Proficiency with Vercel: deployments, ISR, edge functions, preview environments, and environment management.\n\n - Solid grasp of Core Web Vitals, Lighthouse performance auditing, and frontend performance tuning.\n\n - Familiarity with CI/CD pipelines and GitHub Actions.\n\n - Experience managing third-party integrations (video hosting, CRM, marketing tooling).\n\n - Proven ability to manage an external agency or vendor: directing, reviewing, and holding partners accountable.\n\n - Strong project management instincts: you can own delivery end-to-end without a dedicated PM.\n\n - Clear, direct communicator, equally comfortable writing a technical spec and presenting trade-offs to marketing leadership.\n\n - Comfortable operating autonomously in a small, fast-moving environment where priorities shift and pace is relentless.\n\nNice to Have\n\n - Experience improving and scaling an existing web platform, ideally on a headless CMS and Jamstack stack.\n\n - Familiarity with marketing analytics platforms: GA4, Segment, PostHog, Adobe Analytics, or similar.\n\n - Hands-on experience with HubSpot integrations or similar CRM/marketing automation tooling.\n\n - Experience with automated testing frameworks (Jest, Cypress, Playwright).\n\n - Familiarity with monorepo tooling such as Turborepo or Nx.\n\n - Familiarity with AI or developer-tooling products (bonus for Fireworks-adjacent domain knowledge).\n\n - Experience in a founding or first-in-function role at a startup or scale-up.\n\nWho Thrives Here\n\nYou are energised by ownership, not overwhelmed by it. You are comfortable being the only engineer in the room, confident making calls, and able to clearly articulate why. You bridge technical depth with business outcomes and you know how to design systems that unlock collaboration between content, design, and development. You care about craft but know when to move fast.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"cd8233f0-e958-40b5-a9a6-e35ecb9a76a4","title":"Business Development Representative (BDR)","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"San Francisco Bay Area","secondaryLocations":[],"publishedAt":"2025-07-16T19:43:44.297+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/fireworks/cd8233f0-e958-40b5-a9a6-e35ecb9a76a4","applyUrl":"https://jobs.ashbyhq.com/fireworks/cd8233f0-e958-40b5-a9a6-e35ecb9a76a4/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
We're looking for motivated and tech-savvy Business Development Representatives (BDRs) with a strong interest in AI to join our growing sales team. In this role, you’ll play a key part in building a healthy pipeline for our Account Executives by qualifying inbound leads and proactively prospecting into high-value target accounts. This is an opportunity to be at the frontlines of a fast-moving AI company, engaging in thoughtful, technical conversations with a knowledgeable customer base.
The ideal candidate is results driven, exhibits strong intellectual curiosity of the evolving AI space, and can operate in a fast-paced, highly-dynamic start up environment. You should be comfortable initiating outreach, handling nuanced product discussions, and helping prospects understand the impact of generative AI on their business.
Strategically prospect into key accounts across email, calling and Linkedin, communicating Fireworks AI’s unique value proposition
Consistently meet new business opportunity and pipeline generation targets
Craft personalized, tailored outreach through various research methods to prioritize the right accounts and prospects
Qualify and engage inbound leads, ensuring a smooth transition to our Account Executive team
Act as a brand ambassador, educating prospects on the power and potential of our inference solutions
Collaborate with Sales and Marketing to refine messaging and outreach strategies based on market feedback
Stay current on AI/ML trends to conduct informed, relevant conversations with technical and business audiences
Bachelor’s degree or equivalent practical experience
Demonstrated interest in technology sales, with a strong interest AI and machine learning
Excellent communication and interpersonal skills; able to engage confidently with technical stakeholders
Self-motivated and organized, with the ability to manage multiple priorities in a fast-paced environment
Previous startup or entrepreneurial experience, with a proactive and adaptable mindset
Prior experience in a customer facing role, ideally in SaaS, AI, or emerging tech
Familiarity with CRM systems and sales engagement tools (e.g., Salesforce, Outreach, Apollo, etc.)
Degree in engineering, computer science, or a related technical field
Active interest in AI/tech communities with a demonstrated commitment to continuous learning in the space
Fireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in the San Francisco/New York City Area for this role is $85,000 - $100,000 per year.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE\n\nWe're looking for motivated and tech-savvy Business Development Representatives (BDRs) with a strong interest in AI to join our growing sales team. In this role, you’ll play a key part in building a healthy pipeline for our Account Executives by qualifying inbound leads and proactively prospecting into high-value target accounts. This is an opportunity to be at the frontlines of a fast-moving AI company, engaging in thoughtful, technical conversations with a knowledgeable customer base.\n\nThe ideal candidate is results driven, exhibits strong intellectual curiosity of the evolving AI space, and can operate in a fast-paced, highly-dynamic start up environment. You should be comfortable initiating outreach, handling nuanced product discussions, and helping prospects understand the impact of generative AI on their business.\n\n\nKEY RESPONSIBILITIES\n\n - Strategically prospect into key accounts across email, calling and Linkedin, communicating Fireworks AI’s unique value proposition\n\n - Consistently meet new business opportunity and pipeline generation targets\n\n - Craft personalized, tailored outreach through various research methods to prioritize the right accounts and prospects\n\n - Qualify and engage inbound leads, ensuring a smooth transition to our Account Executive team\n\n - Act as a brand ambassador, educating prospects on the power and potential of our inference solutions\n\n - Collaborate with Sales and Marketing to refine messaging and outreach strategies based on market feedback\n\n - Stay current on AI/ML trends to conduct informed, relevant conversations with technical and business audiences\n\n\nMINIMUM QUALIFICATIONS\n\n - Bachelor’s degree or equivalent practical experience\n\n - Demonstrated interest in technology sales, with a strong interest AI and machine learning\n\n - Excellent communication and interpersonal skills; able to engage confidently with technical stakeholders\n\n - Self-motivated and organized, with the ability to manage multiple priorities in a fast-paced environment\n\n\nPREFERRED QUALIFICATIONS\n\n - Previous startup or entrepreneurial experience, with a proactive and adaptable mindset\n\n - Prior experience in a customer facing role, ideally in SaaS, AI, or emerging tech\n\n - Familiarity with CRM systems and sales engagement tools (e.g., Salesforce, Outreach, Apollo, etc.)\n\n - Degree in engineering, computer science, or a related technical field\n\n - Active interest in AI/tech communities with a demonstrated commitment to continuous learning in the space\n\nFireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in the San Francisco/New York City Area for this role is $85,000 - $100,000 per year.\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"0628f651-a8f6-4ef9-beec-6f31c3268c85","title":"Head of GTM Engineering & Systems","department":"Go To Market","team":"Go To Market","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-07-16T00:49:04.242+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/0628f651-a8f6-4ef9-beec-6f31c3268c85","applyUrl":"https://jobs.ashbyhq.com/fireworks/0628f651-a8f6-4ef9-beec-6f31c3268c85/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
Our GTM team is growing 10x. As the leader of GTM Engineering you will set the architecture, drive our AI roadmap, or deliver on the auto-magical future that empowers every customer facing role.
You'll own the full GTM tech stack: Salesforce, CPQ, enrichment, engagement tooling, and the connective tissue between systems serving a growing org of BDRs, AEs, SAs, and managers. You'll also be the person who brings agentic AI from concept to production for our GTM teams, not as an experiment, but as the new operating baseline.
This is a builder and leader role. We're not looking for someone to manage vendors or coordinate rollouts. We want someone who will make hard architectural decisions, ship fast, and raise the bar for what great looks leading a GTM Engineering team.
Own every tool the GTM organization runs on: Salesforce architecture, enrichment layer (Clay, Harmonic, Sumble), routing (LeanData), engagement (Gong, Lemlist, Granola), and the integrations between them. As we scale from roughly 50 to 300+ GTM team members, the architectural decisions you make now are the ones that compound.
We don't have a real CPQ solution today. Deal approvals run through Slack, order forms are built in Google Docs, and the billing handoff is fragile. You'll build a durable quoting and lead-to-revenue architecture from scratch, whether that's native Salesforce CPQ, a purpose-built tool, or a custom solution. The goal: an AE can take a deal from pricing to signed order form without RevOps as a bottleneck.
BDRs, AEs, SAs, sales managers, and RevOps are all under-leveraging AI today. You'll build the workflows that change that: AI-assisted account research, rep-facing deal intelligence, automated pipeline hygiene, manager insights. These should be workflows the team can't imagine working without, not demos.
You're inheriting two strong engineers. You'll grow from there: defining hiring profiles, setting technical standards, building career paths, and maintaining a culture where high-quality, fast-shipping work is the norm.
10+ years in GTM Engineering, Revenue Operations, or Sales Operations at B2B companies; Consumption business model experience strongly desired
5+ years of people management experience
Has architected in Salesforce at real depth: data model, process automation, integrations, governance — and knows how to take advantage of today’s modern CLI/MCP setups
Has driven real world sales rep productivity enhancements measured in $s not time saved.
Has built or rebuilt a quoting or CPQ workflow at meaningful scale
Has led a team and set technical direction, not just managed execution
Track record of building automation that sales reps actually use
Has shipped agentic or AI-native GTM workflows in production (not pilots)
Experience scaling GTM systems through a high-growth phase (Series B to D)
Familiarity with usage-based or consumption pricing models
Has worked at an AI/ML infrastructure, developer tools, or API-first company
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE\n\nOur GTM team is growing 10x. As the leader of GTM Engineering you will set the architecture, drive our AI roadmap, or deliver on the auto-magical future that empowers every customer facing role.\n\nYou'll own the full GTM tech stack: Salesforce, CPQ, enrichment, engagement tooling, and the connective tissue between systems serving a growing org of BDRs, AEs, SAs, and managers. You'll also be the person who brings agentic AI from concept to production for our GTM teams, not as an experiment, but as the new operating baseline.\n\nThis is a builder and leader role. We're not looking for someone to manage vendors or coordinate rollouts. We want someone who will make hard architectural decisions, ship fast, and raise the bar for what great looks leading a GTM Engineering team.\n\n\nWHAT YOU'LL OWN\n\n\n1. GTM TECH STACK AND AI FOUNDATIONS\n\nOwn every tool the GTM organization runs on: Salesforce architecture, enrichment layer (Clay, Harmonic, Sumble), routing (LeanData), engagement (Gong, Lemlist, Granola), and the integrations between them. As we scale from roughly 50 to 300+ GTM team members, the architectural decisions you make now are the ones that compound.\n\n\n2. QUOTING AND LEAD-TO-REVENUE ARCHITECTURE (0 TO 1)\n\nWe don't have a real CPQ solution today. Deal approvals run through Slack, order forms are built in Google Docs, and the billing handoff is fragile. You'll build a durable quoting and lead-to-revenue architecture from scratch, whether that's native Salesforce CPQ, a purpose-built tool, or a custom solution. The goal: an AE can take a deal from pricing to signed order form without RevOps as a bottleneck.\n\n\n3. AGENTIC WORKFLOWS FOR GTM TEAMS\n\nBDRs, AEs, SAs, sales managers, and RevOps are all under-leveraging AI today. You'll build the workflows that change that: AI-assisted account research, rep-facing deal intelligence, automated pipeline hygiene, manager insights. These should be workflows the team can't imagine working without, not demos.\n\n\n4. BUILD AND SCALE THE GTM ENGINEERING TEAM\n\nYou're inheriting two strong engineers. You'll grow from there: defining hiring profiles, setting technical standards, building career paths, and maintaining a culture where high-quality, fast-shipping work is the norm.\n\n\nMINIMUM QUALIFICATIONS\n\n - 10+ years in GTM Engineering, Revenue Operations, or Sales Operations at B2B companies; Consumption business model experience strongly desired\n\n - 5+ years of people management experience\n\n - Has architected in Salesforce at real depth: data model, process automation, integrations, governance — and knows how to take advantage of today’s modern CLI/MCP setups\n\n - Has driven real world sales rep productivity enhancements measured in $s not time saved.\n\n - Has built or rebuilt a quoting or CPQ workflow at meaningful scale\n\n - Has led a team and set technical direction, not just managed execution\n\n - Track record of building automation that sales reps actually use\n\n\nPREFERRED QUALIFICATIONS\n\n - Has shipped agentic or AI-native GTM workflows in production (not pilots)\n\n - Experience scaling GTM systems through a high-growth phase (Series B to D)\n\n - Familiarity with usage-based or consumption pricing models\n\n - Has worked at an AI/ML infrastructure, developer tools, or API-first company\n\n \n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"ccc2b11a-0996-4ed1-b5d6-7da20bbe73bc","title":"Strategic Projects Lead","department":"Product","team":"Product","employmentType":"FullTime","location":"San Mateo","secondaryLocations":[],"publishedAt":"2026-03-02T23:42:27.998+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Mateo"}},"jobUrl":"https://jobs.ashbyhq.com/fireworks/ccc2b11a-0996-4ed1-b5d6-7da20bbe73bc","applyUrl":"https://jobs.ashbyhq.com/fireworks/ccc2b11a-0996-4ed1-b5d6-7da20bbe73bc/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
Fireworks AI is looking for a Strategic Projects Lead to drive high-impact, cross-functional initiatives. We’re looking for a high-agency operator to wear many hats at the intersection of Engineering, Product, and GTM. You’ll be part of the Fireworks product organization where you’ll be an expert in Fireworks’ products and customers. You’ll use that knowledge to drive high-priority, end-to-end projects across the company.
Identify and create new strategic capabilities for Fireworks, like new GTM motions or standardized GTM playbooks
Build deep relationships with customers and lead strategic customer engagements from initial sale to long-term success
Determine product roadmap needs and instrument solutions end-to-end
Own and drive cross-functional initiatives from definition to execution, like partnership creation and model launches
We’re hiring smart hungry people at a variety of experience levels - 1+ years of experience in a high-ownership, fast-paced environment (consulting, product management, software or banking)
Entrepreneurial mindset - excitement about wearing many hats and ability to identify issues and execute quickly
Fluency to engage with senior stakeholders in client and partner organizations
Technical fluency in AI, ML infrastructure, or cloud platforms
Proven track record of leading complex technical or cross-functional initiatives
Analytical capability and comfortability driving decisions quantitatively
Excellent written and verbal communication skills
Bias toward action and high accountability
Experience working on ML infrastructure, inference systems, or AI platforms
Experience supporting enterprise or strategic customers
Prior experience in infrastructure, DevEx, or performance optimization initiatives
Experience operating in high-growth startup environments
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nTHE ROLE:\n\nFireworks AI is looking for a Strategic Projects Lead to drive high-impact, cross-functional initiatives. We’re looking for a high-agency operator to wear many hats at the intersection of Engineering, Product, and GTM. You’ll be part of the Fireworks product organization where you’ll be an expert in Fireworks’ products and customers. You’ll use that knowledge to drive high-priority, end-to-end projects across the company.\n\n\nKEY RESPONSIBILITIES:\n\n - Identify and create new strategic capabilities for Fireworks, like new GTM motions or standardized GTM playbooks\n\n - Build deep relationships with customers and lead strategic customer engagements from initial sale to long-term success \n\n - Determine product roadmap needs and instrument solutions end-to-end\n\n - Own and drive cross-functional initiatives from definition to execution, like partnership creation and model launches\n\n\nMINIMUM REQUIREMENTS:\n\n - We’re hiring smart hungry people at a variety of experience levels - 1+ years of experience in a high-ownership, fast-paced environment (consulting, product management, software or banking)\n\n - Entrepreneurial mindset - excitement about wearing many hats and ability to identify issues and execute quickly \n\n - Fluency to engage with senior stakeholders in client and partner organizations\n\n - Technical fluency in AI, ML infrastructure, or cloud platforms\n\n - Proven track record of leading complex technical or cross-functional initiatives\n\n - Analytical capability and comfortability driving decisions quantitatively \n\n - Excellent written and verbal communication skills\n\n - Bias toward action and high accountability\n\n\nPREFERRED QUALIFICATIONS:\n\n - Experience working on ML infrastructure, inference systems, or AI platforms\n\n - Experience supporting enterprise or strategic customers\n\n - Prior experience in infrastructure, DevEx, or performance optimization initiatives\n\n - Experience operating in high-growth startup environments\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."},{"id":"6e737517-732a-434d-9f18-6b9793bec4ce","title":"Head of Developer Relations","department":"Marketing","team":"Marketing","employmentType":"FullTime","location":"Remote","secondaryLocations":[],"publishedAt":"2026-07-23T16:22:57.669+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":null,"jobUrl":"https://jobs.ashbyhq.com/fireworks/6e737517-732a-434d-9f18-6b9793bec4ce","applyUrl":"https://jobs.ashbyhq.com/fireworks/6e737517-732a-434d-9f18-6b9793bec4ce/application","descriptionHtml":"At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
In the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:
Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog)
Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog)
The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog)
The Head of Developer Relations owns how developers discover, learn, adopt, and champion Fireworks. You build and lead the team that turns Fireworks into the platform developers reach for first when they want to build, fine-tune, and serve frontier open models in production. You set the strategy, run the programs, and build the team that makes our developer community the most informed and most active in AI infrastructure.
You will cultivate developer communities everywhere developers actually are, across the properties we own and the ones we do not, and in person at the events that matter. You will build a team of developer advocates who are genuinely in tune with the frontier and can become credible, hands-on experts in the newest AI developments faster than anyone else in the market. The field moves weekly. Your team has to be one step ahead.
The right person is a builder and an operator who is equally comfortable shipping a demo, speaking on a conference stage, recruiting elite advocates, and reporting developer health metrics to the executive team. You think about developer relations the way a great product leader thinks about a product: who the user is, what they need, how they adopt, and how you measure it.
Reports to: SVP Marketing
Location: Remote (US) with periodic travel to San Mateo HQ and to key events
This role is remote-friendly within the US. You will travel to our San Mateo HQ periodically for team onsites and planning, and you will travel regularly to the conferences, hackathons, meetups, and partner events where the developer community shows up. We will establish a cadence that works for the team and the role.
You cultivate Fireworks developer communities across every surface where developers gather. On our owned properties, that means our docs, blog, examples, cookbooks, Discord, forums, and developer newsletter. On properties we do not own, that means showing up with credibility and consistency on GitHub, X, Reddit, YouTube, Hacker News, and the open-source projects our developers depend on. You meet developers where they are instead of waiting for them to come to us. Success is measured by community growth, engagement, and the share of developer conversations in our category where Fireworks shows up.
You own the in-person strategy that builds real relationships at scale: hackathons, workshops, meetups, conference talks, sponsorships, and developer dinners. You decide where Fireworks shows up, what we say, and who delivers it, and you measure whether it drives durable adoption rather than vanity attendance. You and your team are on stages and at booths, and you build a repeatable playbook so field presence compounds instead of resetting every quarter. Success is measured by qualified developer relationships generated and downstream activation from events.
You hire, develop, and lead a team of developer advocates who can become credible experts on the newest models, techniques, and tools fast. You recruit for raw technical curiosity and learning velocity, not just existing followings, and you build the operating system that keeps the team current as the frontier shifts week to week. That includes a fast-learning loop for new model releases and research, clear ownership areas, content and speaking standards, and a culture where advocates ship and learn in public. Success is measured by team output, the credibility and reach of individual advocates, and how quickly the team produces authoritative material after a major AI development.
You own the content engine that helps developers go from first touch to production: tutorials, quickstarts, reference apps, benchmarks, video, and deep technical writing on inference, fine-tuning, and serving open models. The bar is content that a senior engineer respects and that a new developer can follow. Success is measured by content reach, time to first successful build, and developer-reported usefulness.
You are the voice of the developer inside Fireworks. You channel friction, feature requests, and unmet needs from the community back to product and engineering with clarity and evidence, and you close the loop with developers when we ship. Success is measured by the quality of the developer feedback signal and its influence on the roadmap.
You instrument the developer journey from awareness through signup, first build, and active production usage, and you report developer health to the executive team with definitions everyone trusts. You connect DevRel activity to adoption rather than treating it as unmeasurable. Success is measured by leadership confidence in the developer metrics and by adoption and retention lift attributable to DevRel programs.
Fireworks is consistently present and credible across owned and unowned developer properties, not just our own channels
A repeatable in-person events playbook is driving qualified developer relationships and measurable downstream activation
A high-caliber advocate team is in place and is reliably first to ship authoritative content when a major model or technique drops
The developer funnel from awareness to production usage is instrumented and visible in shared dashboards
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
","descriptionPlain":"ABOUT US:\n\nAt Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.\n\nIn the last few months alone we launched Fireworks Training, partnered with Microsoft Azure Foundry, and published research straight from our production systems. A few examples of what that looks like in practice:\n\n - Frontier RL is cheaper than the mega-cluster narrative suggests: we ran cross-region rollouts using 98% sparse weight deltas and published what we learned. (blog https://fireworks.ai/blog/frontier-rl-is-cheaper-than-you-think)\n\n - Open source agents with frontier advisors: matching frontier performance through training and harness engineering. (blog https://fireworks.ai/blog/open-source-agents-frontier-advisors)\n\n - The fine-tuning bottleneck is not the algorithm: integration friction and iteration speed are what actually stall teams; we documented the patterns across dozens of customer engagements. (blog) https://fireworks.ai/blog/fine-tuning-bottlenecks\n\n\nABOUT THIS ROLE\n\nThe Head of Developer Relations owns how developers discover, learn, adopt, and champion Fireworks. You build and lead the team that turns Fireworks into the platform developers reach for first when they want to build, fine-tune, and serve frontier open models in production. You set the strategy, run the programs, and build the team that makes our developer community the most informed and most active in AI infrastructure.\n\nYou will cultivate developer communities everywhere developers actually are, across the properties we own and the ones we do not, and in person at the events that matter. You will build a team of developer advocates who are genuinely in tune with the frontier and can become credible, hands-on experts in the newest AI developments faster than anyone else in the market. The field moves weekly. Your team has to be one step ahead. \n\nThe right person is a builder and an operator who is equally comfortable shipping a demo, speaking on a conference stage, recruiting elite advocates, and reporting developer health metrics to the executive team. You think about developer relations the way a great product leader thinks about a product: who the user is, what they need, how they adopt, and how you measure it.\n\nReports to: SVP Marketing\n\nLocation: Remote (US) with periodic travel to San Mateo HQ and to key events\n\n\nLOCATION AND WORK STYLE\n\nThis role is remote-friendly within the US. You will travel to our San Mateo HQ periodically for team onsites and planning, and you will travel regularly to the conferences, hackathons, meetups, and partner events where the developer community shows up. We will establish a cadence that works for the team and the role.\n\n\nRESPONSIBILITIES\n\n\nDEVELOPER COMMUNITY, OWNED AND UNOWNED\n\nYou cultivate Fireworks developer communities across every surface where developers gather. On our owned properties, that means our docs, blog, examples, cookbooks, Discord, forums, and developer newsletter. On properties we do not own, that means showing up with credibility and consistency on GitHub, X, Reddit, YouTube, Hacker News, and the open-source projects our developers depend on. You meet developers where they are instead of waiting for them to come to us. Success is measured by community growth, engagement, and the share of developer conversations in our category where Fireworks shows up.\n\n\nIN-PERSON EVENTS AND FIELD PRESENCE\n\nYou own the in-person strategy that builds real relationships at scale: hackathons, workshops, meetups, conference talks, sponsorships, and developer dinners. You decide where Fireworks shows up, what we say, and who delivers it, and you measure whether it drives durable adoption rather than vanity attendance. You and your team are on stages and at booths, and you build a repeatable playbook so field presence compounds instead of resetting every quarter. Success is measured by qualified developer relationships generated and downstream activation from events.\n\n\nBUILDING AND LEADING THE ADVOCATE TEAM\n\nYou hire, develop, and lead a team of developer advocates who can become credible experts on the newest models, techniques, and tools fast. You recruit for raw technical curiosity and learning velocity, not just existing followings, and you build the operating system that keeps the team current as the frontier shifts week to week. That includes a fast-learning loop for new model releases and research, clear ownership areas, content and speaking standards, and a culture where advocates ship and learn in public. Success is measured by team output, the credibility and reach of individual advocates, and how quickly the team produces authoritative material after a major AI development.\n\n\nTECHNICAL CONTENT AND DEVELOPER EDUCATION\n\nYou own the content engine that helps developers go from first touch to production: tutorials, quickstarts, reference apps, benchmarks, video, and deep technical writing on inference, fine-tuning, and serving open models. The bar is content that a senior engineer respects and that a new developer can follow. Success is measured by content reach, time to first successful build, and developer-reported usefulness.\n\n\nDEVELOPER ADVOCACY INTO PRODUCT\n\nYou are the voice of the developer inside Fireworks. You channel friction, feature requests, and unmet needs from the community back to product and engineering with clarity and evidence, and you close the loop with developers when we ship. Success is measured by the quality of the developer feedback signal and its influence on the roadmap.\n\n\nMEASUREMENT AND DEVELOPER FUNNEL\n\nYou instrument the developer journey from awareness through signup, first build, and active production usage, and you report developer health to the executive team with definitions everyone trusts. You connect DevRel activity to adoption rather than treating it as unmeasurable. Success is measured by leadership confidence in the developer metrics and by adoption and retention lift attributable to DevRel programs.\n\n\nWHAT SUCCESS LOOKS LIKE\n\n - Fireworks is consistently present and credible across owned and unowned developer properties, not just our own channels\n\n - A repeatable in-person events playbook is driving qualified developer relationships and measurable downstream activation\n\n - A high-caliber advocate team is in place and is reliably first to ship authoritative content when a major model or technique drops\n\n - The developer funnel from awareness to production usage is instrumented and visible in shared dashboards\n\n\nWHY FIREWORKS AI?\n\n - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.\n\n - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.\n\n - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.\n\n - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.\n\nFireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators."}],"apiVersion":"1"}