About the Team
We build and scale the Compute foundation that powers frontier AI research and products. Our team delivers reliable, efficient, and cost-effective GPU/CPU capacity across world-scale supercomputing systems, enabling researchers and product teams to move quickly. We operate one of the largest GPU fleets in the world, rapidly bringing new infrastructure online across a wide range of providers, hardware types, and generations while integrating it into a single seamless platform at massive scale. We focus on building an intuitive, low-friction system that helps teams experiment faster, innovate faster, and train some of the world’s largest and most advanced models.
About the Role
We’re looking for engineers to help build and operate the next generation of compute infrastructure powering OpenAI’s frontier research. This is an opportunity to work on the large-scale clusters, high-performance networks, and supercomputing systems that enable some of the most advanced AI workloads in the world.
In this role, you’ll combine distributed systems engineering with hands-on infrastructure work across some of our largest data centers. You’ll help scale Kubernetes clusters to massive scale, automate bare-metal bring-up, and build the software layers that make heterogeneous GPU fleets and multi-datacenter supercomputing environments easier to operate.
You’ll work where hardware and software meet, in an environment where speed, efficiency, and reliability are critical. That means solving real-time operational challenges, quickly diagnosing and fixing issues when they arise, and continuously improving automation, resilience, performance, and uptime across the systems that power frontier model training.
In this role, you will:
Spin up and scale large Kubernetes clusters, including automation for provisioning, bootstrapping, and cluster lifecycle management
Build software abstractions that unify multiple clusters and present a seamless interface to training workloads
Own node bring-up from bare metal through firmware upgrades, ensuring fast, repeatable deployment at massive scale
Improve operational metrics such as reducing cluster restart times (e.g., from hours to minutes) and accelerating firmware or OS upgrade cycles
Integrate networking and hardware health systems to deliver end-to-end reliability across servers, switches, and data center infrastructure
Develop monitoring and observability systems to detect issues early and keep clusters stable under extreme load
You might thrive in this role if you:
Have experience operating large-scale compute fleets and enjoy bringing diverse hardware across providers, generations, and environments into one reliable platform
Care deeply about infrastructure efficiency and know how to maximize utilization so every GPU and CPU delivers meaningful work
Bring a strong bias for operational excellence, balancing speed with long-term quality and building systems that improve consistently over time
Focus on solving root causes rather than symptoms, and build trust by eliminating recurring pain points for users
Have experience improving training performance, reducing bottlenecks, and helping workloads run faster and more cost-effectively at scale
Enjoy pushing the limits of scale, from increasing concurrent workloads to enabling larger and more ambitious single-cluster jobs
Build intuitive platforms and tooling that empower researchers, product teams, and operators to self-serve with minimal manual support
Are comfortable working in fast-moving environments where ownership, reliability, and continuous improvement are essential
Qualifications
Experience as an infrastructure, systems, or distributed systems engineer in large-scale or high-availability environments
Strong knowledge of Kubernetes internals, cluster scaling patterns, and containerized workloads
Proficiency in compute infrastructure concepts (compute, networking, storage, security) and in automating cluster or data center operations
Bonus: background with GPU workloads, firmware management, or high-performance computing
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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