Software Engineer, Compute Infrastructure

About the Team:

Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design provision schedule operate and optimize the systems that connect accelerators CPUs networks storage data centers orchestration software agent infrastructure developer tools and observability into one coherent experience for researchers and product teams.

Our work spans the entire stack: capacity planning and cluster lifecycle bare-metal automation distributed systems Kubernetes and scheduling deep system optimization high-performance networking storage fleet health reliability workload profiling benchmarking and the developer experience that lets teams use enormous compute systems with confidence. At this scale small improvements to communication scheduling hardware efficiency or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team and we use this opening to match strong engineers to the problems where they can have the most leverage.

About the Role

We are looking for engineers who want to build the compute platform behind OpenAIs research and products. You may be strongest in low-level systems high-performance computing distributed infrastructure reliability CaaS agent infrastructure developer platforms tooling or the user experience around infrastructure. What matters is that you can reason carefully about complex systems write durable software and raise the quality and velocity of the people around you.

Depending on your background and interests you might work close to hardware close to users on CaaS and agent infrastructure or on the control planes and data planes in between. You could help bring new supercomputing capacity online optimize training workloads from profiler traces and benchmarks improve NCCL and collective communication behavior reason about GPUs NICs topology firmware thermals and failure modes or design abstractions that make heterogeneous clusters feel like one coherent platform.

We do not expect every candidate to have worked at every layer. Some engineers will go deep on systems performance kernel or runtime behavior large-scale networking protocols RDMA NCCL GPU hardware behavior benchmarking scheduling or hardware reliability; others will make the platform more usable through APIs tools workflows and developer experience. The common thread is strong engineering judgment and excitement about making enormous compute systems faster more reliable and easier to use.

This is a general opening for Compute Infrastructure. We will consider candidates for teams across Compute Infrastructure and match you based on your strengths the problems that motivate you and where the infrastructure needs are highest.

Where you might work

• Compute Foundations: Build the low-level platform primitives that make heterogeneous hardware providers and data centers repeatable automatable and operable at scale.

• Fleet / Orchestration: Turn raw capacity into reliable efficient clusters and scheduling systems that researchers and product teams can use with minimal friction and great experience.

• Core Network Engineering: Build and operate the high-performance networking fabrics protocols and observability needed for the largest training and serving workloads.

• Hardware Health and Observability: Detect diagnose remediate and prevent hardware and fleet-health issues so usable compute stays high across providers and accelerator generations.

• Storage: Build scalable performant durable storage abstractions that keep data movement and storage access from becoming a bottleneck to research or products.

• Agent Infrastructure: Build sandboxed execution infrastructure for agentic workloads across research and production with strong isolation reliability and scale.

In this role you will:

• Build and deeply optimize reliable system software for large-scale compute systems that run some of the worlds most demanding AI workloads

• Design and operate infrastructure across accelerators CPUs NICs switches networking protocols storage data centers cluster orchestration scheduling and fleet health

• Profile benchmark and optimize training workloads across compute memory storage networking NCCL and collective communication and cluster scheduling bottlenecks

• Create hardware-aware automation that makes provisioning firmware and driver upgrades incident response and day-to-day operations faster and less error-prone

• Build CaaS agent infrastructure profiling observability benchmarking and platform tools that help researchers product engineers and operators launch debug and optimize workloads with less friction

• Turn operational lessons into better systems stronger abstractions and clearer ownership boundaries across teams

• Collaborate across research engineering security networking hardware and data center teams to make compute capacity more capable and easier to use

You might thrive in this role if you:

• Have built or operated distributed systems infrastructure platforms high-performance computing environments large-scale networking systems Kubernetes clusters developer tools or production systems with demanding reliability requirements

• Enjoy working across layers of the stack and are comfortable moving between software hardware networking systems performance reliability and user needs

• Care about making complex infrastructure understandable observable and usable for the people depending on it

• Can diagnose hard problems under real operational pressure while still investing in long-term engineering quality

• Like building leverage for others whether through APIs automation debugging tools CaaS and agent infrastructure primitives workflow improvements or better platform abstractions

• Are motivated by scale efficiency reliability and disciplined measurement through benchmarks profiles and production evidence

• Communicate clearly take ownership and work well with teams whose constraints and goals differ from your own

Qualifications

• Strong software engineering skills and experience building operating or improving production infrastructure systems

• Experience in one or more relevant areas such as distributed systems operating systems networking protocols RDMA NCCL or collective communication storage Kubernetes scheduling observability reliability engineering high-performance computing GPU infrastructure CaaS agent infrastructure hardware-aware performance optimization benchmarking developer experience or infrastructure tooling

• Ability to debug complex system behavior across software hardware networking and workload layers then turn findings into robust improvements

• Comfort with ambiguity strong ownership and a bias toward practical durable solutions

• Interest in working on infrastructure that directly enables frontier AI research and product impact

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 OpenAIs 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 addition job duties require access to secure and protected information technology systems and related data security obligations.

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IC