About Us
Vast.ai's cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing — reshaping our future for the benefit of humanity. Our mission is to organize, optimize, and orient the world's computation.
We value elegance, ownership, integrity, and continuous learning. You'll have the opportunity to dive into state-of-the-art AI systems while collaborating with a globally distributed team.
About the Role
This role focuses on troubleshooting complex Linux and GPU infrastructure issues across NVIDIA drivers, CUDA, GPU workloads, Ubuntu, Docker, KVM based virtual machines, networking, hardware, BIOS, and firmware. You’ll investigate failures, reproduce issues, identify root causes, and propose practical solutions across the full infrastructure stack.
You’ll also serve as the engineering resource our L1 support team relies on when tickets go beyond frontline triage. You’ll own complex escalations end-to-end, gather technical evidence, coordinate with the appropriate teams, and communicate findings clearly to clients, infrastructure suppliers, and internal teams.
The best engineers in this role don’t just resolve individual issues—they recognize recurring patterns, improve diagnostic tooling, and build runbooks that prevent future incidents. You’ll collaborate directly with the engineering and host support teams on systemic Linux, GPU, and infrastructure problems.
Strong GPU troubleshooting experience, Linux systems knowledge, and technical support skills are the primary requirements. You should be comfortable working autonomously in Ubuntu environments and troubleshooting NVIDIA drivers, CUDA, containers, virtual machines, networking, hardware, and GPU workloads.
Vast.ai users or hosts strongly preferred.
This is a full-time position based in our Westwood, Los Angeles office.
Available schedules:
Monday–Friday: Fully on-site
Sunday–Thursday: Four days on-site and one day working from home
Key Responsibilities
Diagnose and resolve issues across NVIDIA CUDA/GPU drivers, Docker, and KVM virtualization environments
Investigate GPU utilization, container resource constraints, thermal throttling, driver conflicts, and disk I/O bottlenecks
Assist clients and infrastructure suppliers working with TensorFlow, PyTorch, and other GPU-accelerated workloads
Troubleshoot network-layer issues, including VLAN, DNS, DHCP, VPN, NAT, firewall rules, and connectivity failures on host machines
Handle escalated support tickets involving GPU workload failures, container issues, networking problems, account infrastructure, and host-side configuration
Provide managed support for supplier onboarding and ongoing machine management, including installation, configuration, and post setup troubleshooting
Advise suppliers on hardware setup, driver configuration, BIOS and firmware settings, and network configuration for optimal performance
Provide coverage for L1 support overflow during peak periods or incidents
Write and maintain internal runbooks, escalation guides, and knowledge base articles to reduce repeat escalations
Build diagnostic and automation tooling in Python and Bash to reduce manual triage overhead
Collaborate with the engineering and support teams to flag and document systemic or recurring platform issues
You Are
Experienced with Linux, especially Ubuntu, and comfortable troubleshooting from the command line
Someone who enjoys debugging difficult problems and fixing broken systems
Methodical and focused on finding root causes, not just temporary fixes
Able to manage complex tickets independently
A clear written communicator with an interest in AI infrastructure and GPU computing
Must-Haves
Strong Linux systems operations experience with Ubuntu, RHEL/CentOS, or Debian, including networking, storage, services, and permissions
Proficiency with Docker, including container debugging, Docker Compose, image management, cgroup limits, and Docker storage and filesystem troubleshooting
Experience with virtualization platforms such as Proxmox VE, VMware, or similar hypervisors, including VM provisioning and troubleshooting
Strong networking fundamentals, including VLANs, DNS, DHCP, NAT, VPNs, firewall rules, and L2/L3 troubleshooting
Hands-on experience with NVIDIA GPU drivers, CUDA, and GPU workload troubleshooting
Python and Bash scripting skills for automation and diagnostic tooling
Strong written English communication that is clear, professional, and technically precise
Experience providing technical support in a customer-facing or internal help desk environment
Ability to prioritize across a concurrent queue of escalated tickets, triaging by severity and customer impact, balancing reactive resolution against proactive documentation and tooling work, and making clear judgment calls on when to escalate versus own resolution end-to-end
Nice-to-Haves
Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and running GPU-accelerated containers
Monitoring and observability experience (Prometheus, Grafana)
Relevant certifications: RHCSA, CompTIA Linux+, or similar
Knowledge of the Vast.ai platform as a client or infrastructure supplier
After you submit your application, our technical team will review your experience and qualifications. Selected candidates will proceed through the following stages:
15 minutes — Initial Screening (Virtual): A brief conversation about your background, availability, and interest in the role
45 minutes — Experience Interview (Virtual): An introduction to Vast.ai and a deeper discussion of your technical and support experience
2 hours — Meet and Greet and Technical Assessment (On-site): Meet the team and complete an LLM-assisted Linux systems operations assessment
$90,000 – $160,000 + equity + benefits
Vast.ai is hiring across all experience levels with compensation commensurate with background, experience and potential.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
About the Role
We’re hiring a QA Engineer to drive both manual and automated testing across our web applications and backend services in a Linux-first environment. This role is central to shipping reliable, high-performance software for a complex, always-on platform. You’ll work closely with Product and Engineering to define quality standards, catch issues early, and help deliver confident releases.
This role is onsite 5 days a week in our Los Angeles (Westwood) office.
What You'll Do
Execute manual, exploratory, and regression testing for web apps and backend services
Maintain and expand test plans for existing and upcoming features
Design high-signal test cases and build/extend automation where it matters most
Validate requirements and ensure releases are stable and defect-free
Investigate failures, identify root causes, and file clear, actionable tickets
Partner with Product and Engineering on acceptance criteria and release readiness
Minimum Qualifications
3+ years hands-on testing of web applications
Strong knowledge of test methodologies and their corresponding tools
Experience with writing test plans and test cases for assigned features
Experience with test automation
Keen eye for detail
Nice to Have
Passionate about the future of AI
API testing with Postman/Newman or similar
Proficient with Linux
Experience with load testing tools
Benefits
Work 5 days a week from the Vast.ai HQ in Los Angeles (Westwood) in an ambitious, fast-paced, AI-centered startup environment
Health, dental, vision and life insurance coverage
Matching 401K
Pay: $40.00 / hour
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
LOCATION: On-site at our office in San Francisco or Westwood, Los Angeles.
As a Systems Software Engineer, you will work on key performance critical systems such as the daemon which orchestrates every host in our fleet. You will improve the performance, reliability and capability of our infrastructure and containerization technologies including monitoring and telemetry.
Full-time
On-site at either our SF or LA offices
C, C++, Python, Linux
Programming: Strong programming skills in at least one language, ideally C++
Linux and Virtualization: Extensive knowledge of Linux kernel internals, containerization technologies, and virtualization
Isolation Techniques: Deep understanding of workload and network isolation techniques in multi-tenant environments
Cloud Security: Experience in securing and hardening cloud infrastructure, particularly in environments with untrusted workloads
Multi-tenant Security: Strong background in workload and network isolation, network security, and cloud-native security practices
GPU Security: Experience with GPU programming and an understanding of GPU-specific security concerns.
Expand and extend our GPU cloud daemon
Design and deploy market-based resource management systems
Harden code and infrastructure to meet zero‑trust standards
Benchmark, profile, and eliminate bottlenecks across hypervisor, container, and network layers
After submitting your application, our technical team reviews your credentials. If selected, you'll proceed through the following stages:
15 min - Initial screening (virtual)
45 min - Quick dive into Vast, work history (virtual)
45 min - Systems and architectures (virtual)
1 hour - LLM-assisted coding assessment (virtual)
2 hours - Meet and greet with coding assessment (on-site)
Our goal is to complete the interview process in two weeks.
$120,000 – $180,000 + equity + benefits
Vast.ai is hiring across all experience levels with compensation commensurate with background, experience and potential.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
LOCATION: On-site at our office in San Francisco or Westwood, Los Angeles.
As a systems/GPU engineer, you will play a crucial role in developing new kernels and algorithms that can improve inference for AI models. You will help develop new high-performance tensor libraries and auto-optimization tools. Collaborating directly with our technical founder and diverse team, you will enhance the performance and efficiency of our AI systems. Your ability to research and stay on top of cutting-edge papers will be vital in staying up-to-date with the latest advancements in AI model inference and GPU programming techniques.
Full-Time
On-site at either our SF or LA offices
C++/CUDA, GPGPU, Python, Linux
Expertise in systems engineering across the tech stack
Deep understanding of GPU architectures
Strong holistic background in neural network performance and tooling
Published research at top AI conferences
Develop or extend parallel generic GPU libraries and kernels
Help design and deploy market-based resource management systems
Quickly investigate and summarize options for new system architectures
Prototype and evaluate novel state-of-the-art methods/models
Investigate and learn new frameworks and tools
After submitting your application, our technical team reviews your credentials. If selected, you'll proceed through the following stages:
15 min - Initial screening (virtual)
45 min - Quick dive into Vast, work history (virtual)
45 min - Systems and architectures (virtual)
1 hour - LLM-assisted coding assessment (virtual)
2 hours - Meet and greet with coding assessment (on-site)
Our goal is to complete the interview process in two weeks.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
LOCATION: On-site at our office in San Francisco or Westwood, Los Angeles.
As an Agent Research Engineer, you will help advance the highest levels of the tech stack to imbue AI systems with true agency. Collaborating directly with our technical founder and diverse team, we will build the next generation of general learning agents. Possessing and maintaining a wide, deep and holistic knowledge base of cutting-edge research is crucial for advancing the mission. Many are called, but few are chosen.
Full-Time
On-site at either our SF or LA offices
Python, Engrish, LLMs, ANNs, C++/Cuda
Deep expertise in systems engineering across the tech stack
Strong holistic background in machine learning theory and practice
Diverse knowledge of neural architectures/circuits: transformers etc
Published research at top AI conferences
Lead cutting-edge research in AI agents, focusing on memory, reliability, and reasoning
Prototype and evaluate novel state-of-the-art methods/models
After submitting your application, our technical team reviews your credentials. If selected, you'll proceed through the following stages:
Initial screening (virtual 15 minutes)
Quick dive into Vast, systems and architectures (virtual 30 minutes)
LLM assisted coding assessment (virtual 1 hour)
Meet and greet with coding assessment (on-site 2 hours)
Our goal is to complete the interview process in two weeks.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
LOCATION: On-site at our office in San Francisco or Westwood, Los Angeles.
We’re looking for a systems engineer with HPC or parallel programming experience to help scale AI inference. You’ll leverage your knowledge of high-performance systems to optimize GPU performance at the bleeding edge of AI.
Full-Time
On-site at either our SF or LA offices
CUDA/C++, GPGPU, Python, Linux
Design and optimize GPU kernels and tensor libraries
Translate HPC techniques into scalable AI inference solutions
Evaluate emerging architectures and resource management approaches
Collaborate with technical leadership to improve GPU infrastructure efficiency
Advanced C++ (C++17/20 preferred)
Expertise with at least one parallel framework (CUDA, HIP, SYCL, OpenCL, OpenACC, or similar)
Strong background in systems optimization and HPC performance tooling
Familiarity with distributed training/inference frameworks (bonus)
After submitting your application, our technical team reviews your credentials. If selected, you'll proceed through the following stages:
15 min - Initial screening (virtual)
45 min - Quick dive into Vast, work history (virtual)
45 min - Systems and architectures (virtual)
1 hour - LLM-assisted coding assessment (virtual)
2 hours - Meet and greet with coding assessment (on-site)
Our goal is to complete the interview process in two weeks.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
LOCATION: On-site at our office in Westwood, Los Angeles.
We are seeking a skilled Security Engineer to join our dynamic team. We hire people with broad skill sets who also exhibit deep expertise. The ideal candidate will have experience in both offensive and defensive security, strong software development skills, and deep knowledge of Linux systems and containerization. This role provides the opportunity to work on cutting-edge GPU cloud technologies, tackle complex security challenges at scale, and directly enhance the resilience and trustworthiness of our infrastructure and services.
A problem-solver who thrives in a fast-paced environment
Committed to continuous improvement and staying updated with the latest security practices and cloud technologies
A team player with strong communication skills, able to bridge the gap between development and security
Collaborate with Operations Team: Partner with our operations team to ensure compliance with relevant standards such as SOC 2, ISO 27001, and GDPR
Secure Architecture Design: Develop and implement secure architectures for our GPU cloud platform
Security Assessments: Conduct security assessments, threat modeling, code reviews, and penetration testing
Security Improvements: Develop and implement security fixes and improvements in collaboration with engineering teams
Security Tools Management: Implement and manage security tools and systems, including SIEM, WAF, and EDR
Documentation: Create and maintain security documentation, including policies, procedures, and technical guidelines
Security Training: Provide security guidance and training to engineering teams to foster a security-first culture
Incident Response: Participate in incident response activities and contribute to post-incident analysis and improvements
Educational: Bachelor's degree in Computer Science, Cybersecurity, or a related field.
Programming: Strong programming skills in at least one language, ideally Python or C.
Linux and Virtualization: Extensive knowledge of Linux kernel internals, containerization technologies, and virtualization
Isolation Techniques: Deep understanding of workload and network isolation techniques in multi-tenant environments
Cloud Security: Experience in securing and hardening cloud infrastructure, particularly in environments with untrusted workloads
Network and Application Security: Strong background in network security, application security, and cloud-native security practices
Security Testing Tools: Experience with security testing tools and methodologies, such as OWASP, Burp Suite, and static/dynamic analysis tools
Cybersecurity Frameworks: Familiarity with common cybersecurity frameworks, including SOC 2, NIST, and CIS Controls
Security Certifications: Relevant security certifications such as CISSP, CCSP, or OSCP.
DevSecOps Experience: Experience with DevSecOps practices and tools in cloud environments.
Regulatory Compliance: Familiarity with regulatory compliance requirements for operating cloud services.
GPU Security: Experience with GPU programming and an understanding of GPU-specific security concerns.
After submitting your application, our technical team reviews your credentials. If selected, you'll proceed through the following stages:
15 min - Initial screening (virtual)
45 min - Quick dive into Vast, work history (virtual)
45 min - Systems and architectures (virtual)
1 hour - LLM-assisted coding assessment (virtual)
2 hours - Meet and greet with coding assessment (on-site)
Our goal is to complete the interview process in two weeks.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
LOCATION: On-site at our office in San Francisco or Westwood, Los Angeles.
As a Senior Infrastructure Engineer, you will help design and scale the core systems that power Vast.ai’s global GPU marketplace.
You’ll work closely with our founders and core engineering team to extend the underlying compute infrastructure — from GPU provisioning and scheduling to billing, orchestration, and marketplace dynamics.
We’re looking for someone who has previously built large-scale infrastructure platforms — systems with similarities to Vast.ai, or distributed compute orchestration frameworks.
Full-time · On-site at either our SF or LA offices
Python, C++, PostgreSQL, Linux, Docker, KVM, Redis, Terraform, AWS, REST/gRPC APIs
Distributed Systems: Experience building high-throughput backend systems or compute clouds
Compute Orchestration: Familiarity with Docker, or custom scheduling frameworks
GPU Infrastructure: Understanding of GPU provisioning, driver management, and workload scheduling
Billing & Metering: Implemented or integrated usage-based billing and account credit systems
Marketplace Dynamics: Knowledge of dynamic pricing, spot instances, or supply-demand balancing mechanisms
Security & Multi-Tenancy: Experience designing secure, multi-tenant systems in cloud environments
Programming: Strong programming skills in Python and C++; ability to write performant, maintainable, well-architected code
Database Expertise: Comfortable designing schemas and queries for large-scale data systems (PostgreSQL preferred)
Bonus points for:
Experience with GPU security, virtualization, or zero-trust compute isolation
Prior startup experience or end-to-end product ownership
Improve the backend systems that power Vast.ai’s compute marketplace
Integrate GPU provider onboarding, usage tracking, billing, and orchestration APIs
Develop scalable infrastructure for workload scheduling and resource management
Optimize pricing and marketplace logic for efficiency and transparency
Benchmark, profile, and harden systems for performance, reliability, and fault tolerance
Collaborate with product and infrastructure teams to shape the future of decentralized compute
After submitting your application, our technical team reviews your credentials. If selected, you'll proceed through the following stages:
15 min - Initial screening (virtual)
45 min - Quick dive into Vast, work history (virtual)
45 min - Systems and architectures (virtual)
1 hour - LLM-assisted coding assessment (virtual)
2 hours - Meet and greet with coding assessment (on-site)
Our goal is to complete the interview process in two weeks.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
LOCATION: On-site at our office in San Francisco.
You will report directly to Jake Cannell, our founder and CEO, who built the platform and remains deeply involved in technical architecture. You will partner with him to turn technical direction and product priorities into a high-functioning engineering organization: clear ownership, fast delivery, strong code quality, sustainable reliability, and a team that gets better every quarter.
This is not a purely managerial role. The right candidate still enjoys working in the codebase and earns technical trust through judgment, reviews, and occasional critical-path shipping.
You will initially lead a group of approximately 8 engineers across two product/infrastructure teams.
The technical surface area is broad: distributed infrastructure, GPU scheduling and availability, marketplace dynamics, developer experience, payments and billing, reliability, security, and high-throughput backend systems. The role is ideal for someone who likes building both the product and the engineering organization behind it.
Delivery across the customer-facing platform: console, APIs, CLI/SDK, serverless, clusters, billing, and the marketplace engine
Hiring and team design: partner with recruiting to source, assess, close, and onboard senior engineers; maintain a high talent bar; and build the team structure needed to support the roadmap. You will own hiring outcomes for your group.
Engineering quality: review standards, CI, test coverage, incident response, and an on-call rotation that does not burn people out
Team growth: developing engineers into senior engineers and seniors into leads
Execution cadence: turning Jake's technical direction and product priorities into shipped software on predictable timelines, with the minimum process that makes us faster
Ship code in week one
Own delivery for a group of engineers across two to three teams by day 90
Build and execute a hiring plan that results in four or more high-quality senior engineering hires, while preserving the technical bar
Stand up incident review and release processes that engineers actually like
Earn the org's trust the only way that works here: technical judgment demonstrated in the codebase
A strong engineer first: 10+ years building software, with real depth in at least one of distributed systems, cloud infrastructure, GPU/ML systems, or high-throughput backend platforms
An experienced leader: 5+ years managing engineers, including hiring, performance management, and team building at a fast-moving company
Hands-on by choice: you review code daily and still ship
Direct: you give sharp, kind feedback and expect the same
Pragmatic about process: you add structure only where it increases shipping speed, and you cut everything else
Nice to have: marketplace or infrastructure company experience, CUDA/GPU stack familiarity, an open-source track record.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai's cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out-sized, and leadership is earned by shipping excellence.
Vast.ai is seeking a Technical Product Manager to drive the backend our GPU cloud marketplace runs on. This is the software behind every live GPU rental (over 700k transactions a month): the daemon on every host's machines, the orchestration that powers each instance, and the infrastructure and test systems that let us ship it all at high velocity.
The Scale: With over 20k GPUs, our AI cloud platform powers thousands of bleeding-edge training runs and critical production workloads for 120k+ developers all over the planet. This is a product with real scale, real data, and real users from day one. The work you ship moves tangible revenue in weeks, not quarters.
The Challenge: We don't own the GPUs. Thousands of independent hosts price and operate them, and no two machines are alike. Your job is to make that heterogeneous, decentralized supply behave like the top-tier cloud our customers expect: fast, secure, and reliable.
You'll drive the infrastructure, security, and reliability roadmap: sequencing competing priorities, turning non-functional requirements into specs engineering can build, and seeing them through until they ship. You'll own the metrics that prove it worked: platform uptime, fleet reliability, cost-to-serve. Initial focus areas:
Scalability & performance. Keep the core systems fast and ahead of demand as the marketplace grows, from database performance to end-to-end latency.
Security, trust & compliance. Harden the platform against attacks and abuse, and build the compliance roadmap enterprise customers need.
Observability & infra tooling. Give every engineer a clear view of platform health, and every host a clear view of their fleet. Own the metrics, tracing, and tooling behind it.
3+ years as a backend engineer AND 3+ years in product management
Hands-on experience with several of: security, scalability, reliability at scale, infrastructure tooling, distributed systems, observability, abuse/fraud prevention, compliance
Industry experience in one or more of the following areas: software infrastructure, developer tooling (APIs, SDKs, CLIs), AI/ML, cloud computing, GPUs, or two-sided marketplaces
Experience at a fast-paced startup or rapid-growth team
AI-native. You work with AI agents every day, and you want to build the compute layer the AI era runs on.
Deeply technical. You came up as an engineer, and you reason about scalability, security, and efficiency as product concerns, not afterthoughts.
Persuasive across the stack. You can make a technical tradeoff legible to c-suite and a thankless migration compelling to the team doing it.
Biased toward action. You'd rather ship the fix today than present the plan next week.
Python, C++, SQL/PostgreSQL, Redis, Linux, Docker, AWS, Terraform, REST APIs, LLMs/AI agents
Initial screening (virtual)
Deep dive on the role and your experience (virtual)
Live product and technical assessment (virtual)
In person panel interview + product and technical assessment (on-site)
$170,000–$240,000 base depending on experience, plus equity. We're profitable, venture-backed, and growing, so the equity is a stake in a real company with a real valuation, not a lottery ticket.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Ample AI agent budget
LOCATION: On-site at our office in Los Angeles (Westwood).
","descriptionPlain":"ABOUT US\n\nVast.ai's cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.\n\nWe are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out-sized, and leadership is earned by shipping excellence.\n\n\n\n\nABOUT THE ROLE\n\nVast.ai is seeking a Technical Product Manager to drive the backend our GPU cloud marketplace runs on. This is the software behind every live GPU rental (over 700k transactions a month): the daemon on every host's machines, the orchestration that powers each instance, and the infrastructure and test systems that let us ship it all at high velocity.\n\nThe Scale: With over 20k GPUs, our AI cloud platform powers thousands of bleeding-edge training runs and critical production workloads for 120k+ developers all over the planet. This is a product with real scale, real data, and real users from day one. The work you ship moves tangible revenue in weeks, not quarters.\n\nThe Challenge: We don't own the GPUs. Thousands of independent hosts price and operate them, and no two machines are alike. Your job is to make that heterogeneous, decentralized supply behave like the top-tier cloud our customers expect: fast, secure, and reliable.\n\n\n\n\nWHAT YOU'LL OWN\n\nYou'll drive the infrastructure, security, and reliability roadmap: sequencing competing priorities, turning non-functional requirements into specs engineering can build, and seeing them through until they ship. You'll own the metrics that prove it worked: platform uptime, fleet reliability, cost-to-serve. Initial focus areas:\n\n - Scalability & performance. Keep the core systems fast and ahead of demand as the marketplace grows, from database performance to end-to-end latency.\n\n - Security, trust & compliance. Harden the platform against attacks and abuse, and build the compliance roadmap enterprise customers need.\n\n - Observability & infra tooling. Give every engineer a clear view of platform health, and every host a clear view of their fleet. Own the metrics, tracing, and tooling behind it.\n\n\n\n\nIDEAL EXPERIENCE\n\n - 3+ years as a backend engineer AND 3+ years in product management\n\n - Hands-on experience with several of: security, scalability, reliability at scale, infrastructure tooling, distributed systems, observability, abuse/fraud prevention, compliance\n\n - Industry experience in one or more of the following areas: software infrastructure, developer tooling (APIs, SDKs, CLIs), AI/ML, cloud computing, GPUs, or two-sided marketplaces\n\n - Experience at a fast-paced startup or rapid-growth team\n\n\n\n\nYOU ARE\n\n - AI-native. You work with AI agents every day, and you want to build the compute layer the AI era runs on.\n\n - Deeply technical. You came up as an engineer, and you reason about scalability, security, and efficiency as product concerns, not afterthoughts.\n\n - Persuasive across the stack. You can make a technical tradeoff legible to c-suite and a thankless migration compelling to the team doing it.\n\n - Biased toward action. You'd rather ship the fix today than present the plan next week.\n\n\n\n\nTECH STACK\n\nPython, C++, SQL/PostgreSQL, Redis, Linux, Docker, AWS, Terraform, REST APIs, LLMs/AI agents\n\n\n\n\nINTERVIEW PROCESS\n\n - Initial screening (virtual)\n\n - Deep dive on the role and your experience (virtual)\n\n - Live product and technical assessment (virtual)\n\n - In person panel interview + product and technical assessment (on-site)\n\n\n\n\nANNUAL SALARY RANGE\n\n$170,000–$240,000 base depending on experience, plus equity. We're profitable, venture-backed, and growing, so the equity is a stake in a real company with a real valuation, not a lottery ticket.\n\n\n\n\nBENEFITS\n\n - Comprehensive health, dental, vision, and life insurance\n\n - 401(k) with company match\n\n - Meaningful early-stage equity\n\n - Onsite meals, snacks, and close collaboration with founders/tech leaders\n\n - Ambitious, fast-paced startup culture where initiative is rewarded\n\n - Ample AI agent budget\n\n\n\nLOCATION: On-site at our office in Los Angeles (Westwood).","compensation":{"compensationTierSummary":"$170K – $240K • Offers Equity • Offers Bonus","scrapeableCompensationSalarySummary":"$170K - $240K","compensationTiers":[{"id":"c53f7718-c40b-4290-956e-e3835b7fcb70","tierSummary":"$170K – $240K • Offers Equity • Offers Bonus","title":"Base pay","additionalInformation":null,"components":[{"id":"a7332ad1-34bd-4ad9-89f4-a1c6905b3856","summary":"$170K – $240K","compensationType":"Salary","interval":"1 YEAR","currencyCode":"USD","minValue":170000,"maxValue":240000},{"id":"0e685802-dd09-43c9-a7f0-79a128f20e25","summary":"Offers Equity","compensationType":"EquityPercentage","interval":"NONE","currencyCode":null,"minValue":null,"maxValue":null},{"id":"a6e481ff-3bfc-4d9d-8c4c-2682879c8d96","summary":"Offers Bonus","compensationType":"Bonus","interval":"1 YEAR","currencyCode":"USD","minValue":null,"maxValue":null}]}],"summaryComponents":[{"compensationType":"Salary","interval":"1 YEAR","currencyCode":"USD","minValue":170000,"maxValue":240000},{"compensationType":"EquityPercentage","interval":"NONE","currencyCode":null,"minValue":null,"maxValue":null},{"compensationType":"Bonus","interval":"1 YEAR","currencyCode":"USD","minValue":null,"maxValue":null}]}},{"id":"4bad56d6-a3e3-4b25-8800-f37410791955","title":"Technical Support Engineer II (Linux)","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"Los Angeles","shouldDisplayCompensationOnJobPostings":true,"secondaryLocations":[],"publishedAt":"2026-07-17T23:11:31.991+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Los Angeles"}},"jobUrl":"https://jobs.ashbyhq.com/vastai/4bad56d6-a3e3-4b25-8800-f37410791955","applyUrl":"https://jobs.ashbyhq.com/vastai/4bad56d6-a3e3-4b25-8800-f37410791955/application","descriptionHtml":"About Us
Vast.ai's cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing — reshaping our future for the benefit of humanity. Our mission is to organize, optimize, and orient the world's computation.
We value elegance, ownership, integrity, and continuous learning. You'll have the opportunity to dive into state-of-the-art AI systems while collaborating with a globally distributed team.
About the Role
This is a technical support role focused on escalated infrastructure issues that go beyond frontline triage. You'll be the engineering resource our L1 support team leans on when tickets get complex: diagnosing and resolving issues across the full stack — hardware/BIOS/firmware, networking, Ubuntu, Docker, NVIDIA CUDA/GPU, and virtualization (KVM).
You'll handle higher-complexity issues, own escalation resolution end-to-end, and contribute to internal documentation and runbooks. The best engineers in this role don't just resolve tickets — they build the tooling and runbooks that eliminate recurring ones. You'll collaborate directly with the engineering team and host support team on systemic issues.
Strong technical depth and support experience are the primary requirements. You should be comfortable working autonomously across Ubuntu environments, diagnosing container and GPU issues, and communicating findings clearly to both technical and non-technical audiences.
Vast.ai users or hosts strongly preferred.
This role is full-time and onsite in our office in Westwood (LA)
Schedule: Sunday - Thursday.
Key Responsibilities
Handle escalated support tickets, including GPU workload failures, container issues, networking problems, account infrastructure, and host-side configuration
Diagnose and resolve issues across Docker, NVIDIA CUDA/GPU drivers, and virtualization environments (KVM)
Troubleshoot network-layer issues: VLAN, DNS, DHCP, VPN, NAT, firewall rules, and connectivity failures on host machines
Investigate performance issues on GPU utilization, container resource constraints, thermal throttling, driver conflicts, disk I/O bottlenecks
Advise suppliers (hosts) on installation best practices — hardware setup, driver configuration, BIOS/firmware settings, and network configuration for optimal performance
Provide managed support for supplier onboarding and ongoing machine management, acting as a technical resource through installation, configuration, and post-setup troubleshooting
Write and maintain internal runbooks, escalation guides, and knowledge base articles to reduce repeat escalations
Build diagnostic and automation tooling in Python and Bash to reduce manual triage overhead
Collaborate with the engineering team and infrastructure support team to flag and document systemic or recurring platform issues
Assist clients and infrastructure suppliers working with AI frameworks (TensorFlow, PyTorch) and GPU-accelerated workloads
Provide coverage for L1 support team overflow during peak periods or incidents, per a defined on-call rotation
You Are
Fluent in Linux — you navigate systems, read logs, and solve problems from the command line without hesitation
Methodical and thorough: you gather data, dig into root causes, and don't settle for surface-level fixes
A self-starter who can manage a queue of complex tickets with minimal supervision
Adaptable to a defined on-call rotation which may include weekend coverage
A clear written communicator: able to explain technical findings and write useful internal documentation
Genuinely curious about AI infrastructure, GPU computing, and distributed systems
Must-Haves
Solid Linux SysOps experience: Ubuntu Server, RHEL/CentOS, Debian; comfortable with systems, networking, storage, and permissions
Proficiency with Docker: container debugging, Docker Compose, image management, cgroup resource limits, Docker storage/filesystem management
Experience with virtualization: Proxmox VE, VMware, or similar hypervisors; provisioning and troubleshooting VMs
Networking fundamentals: VLAN, DNS, DHCP, NAT, VPN, firewall rules, and general L2/L3 troubleshooting
Hands-on experience with NVIDIA GPU drivers, CUDA, and GPU workload troubleshooting (essential)
Scripting in Python and Bash for automation and diagnostic tooling
Strong English written communication: clear, professional, and technically precise
Experience providing technical support in a customer-facing or internal helpdesk context
Ability to prioritize across a concurrent queue of escalated tickets, triaging by severity and customer impact, balancing reactive resolution against proactive documentation and tooling work, and making clear judgment calls on when to escalate versus own resolution end-to-end
Nice-to-Haves
Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and running GPU-accelerated containers
Monitoring and observability experience (Prometheus, Grafana)
Relevant certifications: RHCSA, CompTIA Linux+, or similar
Knowledge of the Vast.ai platform as a client or infrastructure supplier
$90,000 – $150,000 + equity + benefits
Vast.ai is hiring across all experience levels with compensation commensurate with background, experience and potential.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
About Us
Vast.ai's cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing — reshaping our future for the benefit of humanity. Our mission is to organize, optimize, and orient the world's computation.
We value elegance, ownership, integrity, and continuous learning. You'll have the opportunity to dive into state-of-the-art AI systems while collaborating with a globally distributed team.
About the Role
This is a systems operations support role focused on deep-diving into escalated infrastructure issues that go beyond frontline triage. You’ll be the engineering resource our L1 support team relies on when tickets become complex, investigating and resolving issues across the full infrastructure stack—including hardware, BIOS and firmware, networking, Ubuntu, Docker, NVIDIA CUDA and GPUs, and KVM virtual machines.
You’ll own complex escalations end-to-end: gathering evidence, reproducing issues, identifying the root cause, proposing solutions, and working with the appropriate teams to bring each issue to resolution. The best engineers in this role don’t just resolve individual tickets—they identify recurring patterns, improve operational tooling, and build runbooks that prevent future incidents. You’ll collaborate directly with the engineering and host support teams on systemic infrastructure issues.
Strong Linux systems knowledge, technical depth, and support experience are the primary requirements. You should be comfortable working autonomously in Ubuntu environments, troubleshooting hardware, networking, containers, virtual machines, and GPU workloads, and clearly communicating your findings and proposed solutions to both technical and non-technical audiences.
Vast.ai users or hosts strongly preferred.
This is a full-time position based in our Westwood, Los Angeles office.
Available schedules:
Monday–Friday: Fully on-site
Sunday–Thursday: Four days on-site and one day working from home
Key Responsibilities
Handle escalated support tickets involving GPU workload failures, container issues, networking problems, account infrastructure, and host-side configuration
Provide managed support for supplier onboarding and ongoing machine management, acting as a technical resource through installation, configuration, and post-setup troubleshooting
Assist clients and infrastructure suppliers working with TensorFlow, PyTorch, and other GPU-accelerated workloads
Provide coverage for L1 support overflow during peak periods or incidents
Diagnose and resolve issues across Docker, NVIDIA CUDA/GPU drivers, and KVM virtualization environments
Troubleshoot network-layer issues, including VLAN, DNS, DHCP, VPN, NAT, firewall rules, and connectivity failures on host machines
Investigate performance issues involving GPU utilization, container resource constraints, thermal throttling, driver conflicts, and disk I/O bottlenecks
Advise suppliers on installation best practices, including hardware setup, driver configuration, BIOS/firmware settings, and network configuration for optimal performance
Write and maintain internal runbooks, escalation guides, and knowledge base articles to reduce repeat escalations
Build diagnostic and automation tooling in Python and Bash to reduce manual triage overhead
Collaborate with the engineering and support teams to flag and document systemic or recurring platform issues
You Are
Experienced with Linux, especially Ubuntu, and comfortable troubleshooting from the command line
Someone who enjoys debugging difficult problems and fixing broken systems
Methodical and focused on finding root causes, not just temporary fixes
Able to manage complex tickets independently
A clear written communicator with an interest in AI infrastructure and GPU computing
Must-Haves
Strong Linux systems operations experience with Ubuntu, RHEL/CentOS, or Debian, including networking, storage, services, and permissions
Proficiency with Docker, including container debugging, Docker Compose, image management, cgroup limits, and Docker storage and filesystem troubleshooting
Experience with virtualization platforms such as Proxmox VE, VMware, or similar hypervisors, including VM provisioning and troubleshooting
Strong networking fundamentals, including VLANs, DNS, DHCP, NAT, VPNs, firewall rules, and L2/L3 troubleshooting
Hands-on experience with NVIDIA GPU drivers, CUDA, and GPU workload troubleshooting
Python and Bash scripting skills for automation and diagnostic tooling
Strong written English communication that is clear, professional, and technically precise
Experience providing technical support in a customer-facing or internal help desk environment
Ability to prioritize across a concurrent queue of escalated tickets, triaging by severity and customer impact, balancing reactive resolution against proactive documentation and tooling work, and making clear judgment calls on when to escalate versus own resolution end-to-end
Nice-to-Haves
Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and running GPU-accelerated containers
Monitoring and observability experience (Prometheus, Grafana)
Relevant certifications: RHCSA, CompTIA Linux+, or similar
Knowledge of the Vast.ai platform as a client or infrastructure supplier
After you submit your application, our technical team will review your experience and qualifications. Selected candidates will proceed through the following stages:
15 minutes — Initial Screening (Virtual): A brief conversation about your background, availability, and interest in the role
45 minutes — Experience Interview (Virtual): An introduction to Vast.ai and a deeper discussion of your technical and support experience
2 hours — Meet and Greet and Technical Assessment (On-site): Meet the team and complete an LLM-assisted Linux systems operations assessment
$90,000 – $160,000 + equity + benefits
Vast.ai is hiring across all experience levels with compensation commensurate with background, experience and potential.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We are past the search for product-market fit and are building the financial infrastructure needed to scale a high-volume, API-native marketplace for AI compute.
LOCATION: On-site at our office in Westwood, Los Angeles.
This is a hands-on leadership role. Today, you will be the senior in-house owner of accounting and finance operations, partnering with the COO, fractional CFO, external accounting, tax, payroll, audit, and systems advisors, and engineering, data, and product teams. You will build a scalable, automation-first function: not by adding process for its own sake, and not by assuming every problem requires headcount, but by designing clean policies, strong controls, and systems that make high-volume finance operations reliable. As the company scales, you will have the mandate and budget to hire and lead a team where specialization, volume, or control needs justify it.
Lead GAAP conversion and audit readiness. Own the transition from cash to accrual accounting, establish GAAP-compliant financial statements and supporting policies, and prepare the company for its first audit in coordination with external advisors.
Own the close and accounting operations. Run the monthly close and core finance operations, including accounts receivable and collections, accounts payable and vendor management, payroll, reconciliations, approval workflows, and close documentation.
Build marketplace revenue accounting. Own accounting for usage-based, multi-party marketplace transactions, including ASC 606 analysis, gross-versus-net principal-agent conclusions, customer credits, refunds, chargebacks, deferred revenue, host/provider payouts, payment processor reconciliations, and unit-economics reporting.
Design payout and cash controls. Create reliable controls over customer funds, host payouts, credits, disputes, fraud adjustments, bank activity, and the reconciliation of product, billing, payments, payout, and general ledger data.
Lead tax and compliance operations. Manage outside tax specialists and internal stakeholders for all tax related matters.
Stand up systems and controls. Select, implement, or improve the finance stack across ERP, billing-to-cash, AP automation, payout tooling, tax engines, payroll, equity administration, and reporting.
Own financial reporting and planning inputs. Run monthly financial reporting, cash visibility, actuals analysis, and operating metrics. Partner with the COO and fractional CFO on the quarterly forecast, annual budget, board and investor reporting, and equity and stock-based-compensation accounting, including ASC 718 and 409A coordination.
Partner cross-functionally. Work closely with engineering, product, data, legal, and operations to translate product and transaction logic into accounting policies, financial controls, and scalable reporting.
Build the future team. Define the roadmap for when to hire versus automate across accounting operations, revenue accounting, tax, systems, and FP&A support, then recruit and lead that team as the company scales.
Cash-to-accrual conversion completed, with a predictable monthly GAAP close and written accounting policies in place.
Audit-ready financial statements, support schedules, reconciliations, and process documentation delivered with external advisors.
Revenue recognition, gross-versus-net conclusions, host payout accounting, customer credits, refunds, and marketplace reconciliations operating reliably at scale.
Finance systems roadmap implemented across ERP, billing-to-cash, payouts, AP automation, tax compliance, payroll, equity administration, and reporting.
Indirect-tax compliance live across the jurisdictions that matter, with clear ownership between Vast.ai and outside tax specialists.
Monthly reporting, cash visibility, forecast inputs, budget process, and unit-economics reporting used by leadership for operating decisions.
A practical hiring and automation roadmap in place for the next stage of finance team growth.
Active CPA. CPA in good standing with strong technical accounting judgment and practical GAAP experience.
Controller-level operating experience. 8+ years in accounting and finance, including 2+ years at Controller, Assistant Controller, or equivalent senior accounting leadership level in a high-growth company.
Close and reporting ownership. Hands-on experience owning or materially leading the monthly close, account reconciliations, financial statement preparation, and accounting operations in a private company environment.
Marketplace or usage-based business model exposure. Direct experience with a marketplace, platform, SaaS, usage-based, fintech, payments, infrastructure, or other multi-party transactional business.
Revenue accounting foundation. Working knowledge of ASC 606, gross-versus-net principal-agent analysis, deferred revenue, customer credits, refunds, payouts, and unit-economics reporting.
US indirect-tax exposure. Practical experience with multi-state US indirect-tax compliance and the judgment to manage outside specialists effectively.
Systems and data orientation. Comfort implementing or operating ERP, billing, payment, payout, payroll, tax, and reporting systems, and reconciling operational data to the general ledger.
Automation-first mindset. Demonstrated ability to use systems, AI tools, workflows, and controls to reduce manual work without sacrificing accuracy, auditability, or judgment.
Builder mindset. A hands-on operator who can move from blank page to operating reality, communicate clearly with non-finance teams, and build structure without slowing the company down.
Public-accounting experience at a Big 4, national, or top regional firm, paired with in-house operating experience.
10–12 years of total accounting and finance experience, including time as the first or most senior in-house accounting leader at a high-growth company.
Hands-on experience leading or co-leading a cash-to-accrual conversion and first-audit readiness process.
Marketplace-facilitator analysis, international VAT and GST exposure, host/provider withholding, and 1099 and 1042-S information reporting experience.
Experience implementing or upgrading an ERP, plus tools such as Stripe, Adyen, Avalara, Vertex, TaxJar, Tipalti, Bill.com, Ramp, Brex, Rippling, Carta, or similar systems.
Demonstrated use of AI and automation tooling in finance operations, especially AP automation, close management, reconciliations, exception review, or payout workflows.
Equity and stock-based-compensation accounting experience, including ASC 718 and 409A coordination.
Comfort working with SQL, data warehouses, BI tools, or product analytics teams to reconcile operational events to financial reporting.
This is a full-time on-site role based in Los Angeles. The role requires close collaboration with the COO, founders, engineering, product, data, and operations teams, especially during close, systems implementation, audit-readiness, and tax-compliance buildout.
After you apply, our team reviews your credentials. If selected, you will proceed through the following stages:
15 minutes: Initial screening, virtual.
45 minutes: Deep dive into Vast.ai’s business model, financials, and your background, virtual.
60 minutes: Structured technical case covering revenue recognition, marketplace reconciliations, and monthly financial reporting.
2 hours: On-site working session with leadership based on a representative Vast.ai finance problem, with confidential or sensitive details redacted.
We aim to complete the interview process in about 2 to 4 weeks.
Comprehensive health, dental, vision, and life insurance
401(k) with company match
Meaningful early-stage equity
Onsite meals, snacks, and close collaboration with founders/tech leaders
Ambitious, fast-paced startup culture where initiative is rewarded
Vast.ai runs one of the largest GPU marketplaces in the world. Over 20,000 GPUs, from RTX 4090s up to B300s, rented by more than 25,000 customers a month who train, fine-tune, and serve AI models on them. We are profitable, the team is flat, and we ship quickly. Your application goes straight to the hiring team.
This is an engineering job that happens in public. You will be our heaviest user.
Most of your week goes to renting GPUs on Vast and building things on them. Serving open source models with vLLM and SGLang. Fine-tuning. Running ComfyUI pipelines. Keeping live inference endpoints up, including token endpoints on markets like OpenRouter. Writing the example repos, Docker templates, and benchmarks that other developers copy.
The rest of your week is spent showing your work. Short videos, technical write-ups, answers in Discord and on Reddit, hackathons. You are not building the Vast product. You are using it harder than any of our customers, in the open, and reporting back everything that breaks.
If you want a content calendar and a campaign plan, this is the wrong job. If you already spin up GPUs on weekends because you want to see whether the new model actually runs, keep reading.
Run real workloads on Vast every week. Deploy, fine-tune, and serve open source models, and keep live endpoints running.
Build public example repos, Docker templates, and benchmarks that developers can clone and use.
Turn what you build into teaching: guides, short videos, talks, livestreams.
Be the most technically credible voice in our Discord, on Reddit, and on X.
Represent Vast at hackathons and conferences, roughly one trip a month.
Report the friction, the breakage, and the missing docs straight to engineering and product.
You can take an open source model from Hugging Face to a running endpoint on rented GPUs with nobody helping you. Linux, Docker, Python, SSH.
You can debug the GPU stack. Driver and CUDA mismatches, out of memory errors, and multi-GPU configuration including NCCL and topology issues do not scare you.
Public proof of work you have shipped. A GitHub profile, technical writing, or live projects. We will ask you to walk us through code you wrote and explain the parts that went wrong.
You work without a roadmap and prefer it that way. Nobody here will hand you a task list.
You can explain a hard thing clearly, in writing and out loud.
Content or side projects that found a real audience.
Previous developer relations, community, or customer-facing work. Useful here, but it is a bonus and not the job.
vLLM or SGLang internals, distributed training with FSDP or DeepSpeed, CUDA.
Time at a cloud, GPU, AI infrastructure, or developer tools company.
Ship several public example projects on Vast, including at least one live serving endpoint.
Publish benchmarks or guides that developers actually use and pass around.
Become the recognizable technical voice in our community channels.
Represent Vast at a sponsored hackathon.
$160,000 to $200,000 base, plus equity and bonus. Health, dental, vision, and life insurance. 401(k) with company match. Meals on site. Travel and conference budget. This role is on site in San Francisco or Los Angeles.
","descriptionPlain":"ABOUT VAST.AI\n\nVast.ai runs one of the largest GPU marketplaces in the world. Over 20,000 GPUs, from RTX 4090s up to B300s, rented by more than 25,000 customers a month who train, fine-tune, and serve AI models on them. We are profitable, the team is flat, and we ship quickly. Your application goes straight to the hiring team.\n\n\n\n\nTHE ROLE\n\nThis is an engineering job that happens in public. You will be our heaviest user.\n\nMost of your week goes to renting GPUs on Vast and building things on them. Serving open source models with vLLM and SGLang. Fine-tuning. Running ComfyUI pipelines. Keeping live inference endpoints up, including token endpoints on markets like OpenRouter. Writing the example repos, Docker templates, and benchmarks that other developers copy.\n\nThe rest of your week is spent showing your work. Short videos, technical write-ups, answers in Discord and on Reddit, hackathons. You are not building the Vast product. You are using it harder than any of our customers, in the open, and reporting back everything that breaks.\n\nIf you want a content calendar and a campaign plan, this is the wrong job. If you already spin up GPUs on weekends because you want to see whether the new model actually runs, keep reading.\n\n\n\n\nWHAT YOU'LL DO\n\n - Run real workloads on Vast every week. Deploy, fine-tune, and serve open source models, and keep live endpoints running.\n\n - Build public example repos, Docker templates, and benchmarks that developers can clone and use.\n\n - Turn what you build into teaching: guides, short videos, talks, livestreams.\n\n - Be the most technically credible voice in our Discord, on Reddit, and on X.\n\n - Represent Vast at hackathons and conferences, roughly one trip a month.\n\n - Report the friction, the breakage, and the missing docs straight to engineering and product.\n \n\n\nWHAT WE NEED TO SEE\n\n - You can take an open source model from Hugging Face to a running endpoint on rented GPUs with nobody helping you. Linux, Docker, Python, SSH.\n\n - You can debug the GPU stack. Driver and CUDA mismatches, out of memory errors, and multi-GPU configuration including NCCL and topology issues do not scare you.\n\n - Public proof of work you have shipped. A GitHub profile, technical writing, or live projects. We will ask you to walk us through code you wrote and explain the parts that went wrong.\n\n - You work without a roadmap and prefer it that way. Nobody here will hand you a task list.\n\n - You can explain a hard thing clearly, in writing and out loud.\n \n\n\nNICE TO HAVE\n\n - Content or side projects that found a real audience.\n\n - Previous developer relations, community, or customer-facing work. Useful here, but it is a bonus and not the job.\n\n - vLLM or SGLang internals, distributed training with FSDP or DeepSpeed, CUDA.\n\n - Time at a cloud, GPU, AI infrastructure, or developer tools company.\n \n\n\nFIRST 90 DAYS\n\n - Ship several public example projects on Vast, including at least one live serving endpoint.\n\n - Publish benchmarks or guides that developers actually use and pass around.\n\n - Become the recognizable technical voice in our community channels.\n\n - Represent Vast at a sponsored hackathon.\n \n\n\nCOMPENSATION & BENEFITS\n\n$160,000 to $200,000 base, plus equity and bonus. Health, dental, vision, and life insurance. 401(k) with company match. Meals on site. Travel and conference budget. This role is on site in San Francisco or Los Angeles.","compensation":{"compensationTierSummary":"$160K – $200K • Offers Equity • Offers Bonus","scrapeableCompensationSalarySummary":"$160K - $200K","compensationTiers":[{"id":"ddac6091-583a-484e-b1b2-c324b355d34c","tierSummary":"$160K – $200K • Offers Equity • Offers Bonus","title":"Competitive Compensation","additionalInformation":null,"components":[{"id":"43bb917c-1720-4406-b5cd-77b950ec722a","summary":"$160K – $200K","compensationType":"Salary","interval":"1 YEAR","currencyCode":"USD","minValue":160000,"maxValue":200000},{"id":"3185ac75-a2d8-43b4-8df6-6e81215c2850","summary":"Offers Equity","compensationType":"EquityPercentage","interval":"NONE","currencyCode":null,"minValue":null,"maxValue":null},{"id":"090bc84f-77e6-40a7-8ecc-32af8710634a","summary":"Offers Bonus","compensationType":"Bonus","interval":"1 YEAR","currencyCode":"USD","minValue":null,"maxValue":null}]}],"summaryComponents":[{"compensationType":"Salary","interval":"1 YEAR","currencyCode":"USD","minValue":160000,"maxValue":200000},{"compensationType":"EquityPercentage","interval":"NONE","currencyCode":null,"minValue":null,"maxValue":null},{"compensationType":"Bonus","interval":"1 YEAR","currencyCode":"USD","minValue":null,"maxValue":null}]}},{"id":"c3012401-acce-4c91-ac79-fc339be47e62","title":"Head of Sales","department":"Sales","team":"Sales","employmentType":"FullTime","location":"Los Angeles","shouldDisplayCompensationOnJobPostings":false,"secondaryLocations":[],"publishedAt":"2026-09-07T23:40:14.424+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Los Angeles"}},"jobUrl":"https://jobs.ashbyhq.com/vastai/c3012401-acce-4c91-ac79-fc339be47e62","applyUrl":"https://jobs.ashbyhq.com/vastai/c3012401-acce-4c91-ac79-fc339be47e62/application","descriptionHtml":"Head of Sales
Lead and scale the team selling both sides of Vast.ai's GPU marketplace—with revenue on track to 10x. Player-manager role reporting to the COO, onsite 5 days a week in Westwood, Los Angeles.
Los Angeles, CA · On-site · Full-time · $140K–$185K base · ~$260K–$375K OTE · Equity
Vast.ai runs one of the leading GPU compute exchanges in the world, and we're moving fast in one of the most competitive markets in tech. Demand for GPUs is exploding, our product surface is expanding, and sales are on track to 10x. We're looking for a hands-on Head of Sales to seize that moment. This role reports directly to the COO.
You will initially lead two quota-carrying reps across enterprise demand and strategic supply. Over the next 12–18 months, you will determine the appropriate team structure, hire against demonstrated capacity, and turn our early sales motion into a repeatable operating system.
This is a player-manager role at an inflection point. You will spend the majority of your time coaching reps, running sales operations, and building the tooling and incentive systems that let us scale without breaking. The revenue engine and team already exist; your mandate is to grow them aggressively. As our product offerings and outreach expand, you'll be the person who scales the sales org behind it—growing the team, the pipeline, and the playbook in lockstep with the business. This role is onsite 5 days a week in our Westwood, Los Angeles office.
What You Will Do
Coach and develop our existing demand (renter) and supply (host) sales reps—the majority of your time
Scale the team: hire, onboard, and ramp new reps as we grow headcount alongside revenue
Expand and sharpen our sales outreach across an increasing set of product offerings
Run day-to-day sales operations: pipeline hygiene, forecasting, and CRM discipline in HubSpot
Investigate, select, and own the sales tool stack; keep it lean and high-signal
Design and manage commission structures and comp plans, including pod-based incentives, deal splits, and escalators
Set, own, and track sales goals and quotas across a growing team
Personally own a small book of strategic and brokered accounts to stay close to the deal
Partner with Marketing, Product, and Engineering to align go-to-market and feed the roadmap
What We Need
Startup experience (required)
8+ years in B2B sales, including 3+ years directly coaching and managing quota-carrying reps
Experience in cloud hosting, data center infrastructure, or GPU rental / compute markets
Track record of scaling a sales team and revenue in a fast-moving environment
Strong forecasting, pipeline, and sales-operations discipline
Hands-on fluency with CRM (HubSpot) and the modern sales tool stack
Experience designing or managing commission and quota structures
Comfort operating in ambiguity and building process where little exists
Keen eye for detail and a bias toward systems over heroics
Nice To Have
Experience with consumption-based revenue, marketplace attribution, or other usage-driven sales models.
Two-sided marketplace sales experience
Technical fluency with GPUs, ML infrastructure, or developer-facing products
RevOps depth: comp automation, attribution, and forecasting tooling
Passionate about the future of AI
What Success Looks Like
Within 90 days: establish trustworthy pipeline, attribution, forecasting, and weekly operating cadences.
Within six months: complete the initial team and territory design, make priority hires, and establish distinct demand and supply playbooks.
Within 12 months: deliver the agreed sales-attributed margin target, materially improve rep productivity, and produce a reliable capacity and hiring plan for the next stage.
Benefits
Paid vacation, holidays, and parental leave
Office meals and snacks
Westwood proximity/transit stipend
401(k) with company match
Stock options with standard vesting
About Us
Vast.ai’s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing—reshaping our future for the benefit of humanity.
We value curiosity, ownership, and continuous learning. You’ll have the opportunity to dive into state-of-the-art AI systems while collaborating with a globally distributed team. We encourage and support growth into specialized or leadership tracks as our startup continues to scale.
About the Role
This is a high-volume, customer-facing L1 support role. You will be the first voice our customers and GPU hosts hear when something goes wrong — and how you handle that moment matters as much as whether you can technically diagnose it.
Success in this role is roughly equal parts people skills and technical knowledge. If you're a strong communicator who happens to know Linux and Docker, you'll thrive here. If you're deeply technical but find customer interaction draining or difficult, this likely isn't the right fit.
You will handle a steady stream of chat and email tickets — diagnosing GPU rental issues, helping clients run AI workloads, supporting hosts, and escalating what you can't resolve. Previous experience in a customer support or technical support role is strongly preferred.
Vast.ai users or hosts strongly preferred.
This is a full-time, remote position anywhere in Vietnam. Ability to work evenings, weekends and holidays is highly preferred.
Vast.ai users or hosts strongly preferred.
Key Responsibilities
50% General Customer Support / 50% Technical Support
Respond to a high volume of customer and host inquiries via chat and email with professionalism and clarity
Troubleshoot L1 issues related to GPU rentals, Docker containers, Linux environments, and account related questions
Set clear expectations, communicate status updates, and follow up until issues are resolved
Identify, document, and escalate issues that require L2/engineering attention
Maintain and improve support documentation and internal knowledge base articles
You Are
Genuinely energized by helping people — you don't just tolerate customer interaction, you're good at it
A clear, confident written communicator — especially under pressure or with frustrated customers
Patient and methodical when working through ambiguous or technically complex problems
Comfortable working independently in a fast-paced, remote environment including weekends & holidays
Detail-oriented with strong follow-through — you close the loop, you don't drop tickets
Curious about AI, GPU computing, or cloud infrastructure
Must-haves
Previous experience in customer support or technical support (B2C or B2B)
Strong English written communication — clear, professional, and empathetic in tone
Linux SysOps fundamentals — comfort with the command line, file systems, permissions
Working knowledge of Network and Docker Troubleshooting
Demonstrated ability to handle frustrated or confused customers constructively
Nice-to-haves
Familiarity with GPU drivers (NVIDIA CUDA) and GPU workloads
Experience with AI/ML frameworks (TensorFlow, PyTorch)
Prior experience in a cloud or infrastructure support role
Knowledge of the Vast.ai platform as a client or host
Familiarity with VMs and virtualization
Benefits
Competitive salary
100% salary during probation period
Yearly Performance Bonus
Annual leave as per regulations
Health Insurance
Reimbursement for approved work expenses
Fast growing, ambitious startup environment