Software Engineer, Compute Foundations
OpenAI
- Pay
- $255k–$490k
- Workplace
- On-site
- Location
- San Francisco · California · United States
- First seen
- 2 hours ago
- Last seen
- 2 hours ago
- Board
- Ashby
Summary
ABOUT THE TEAM Compute Foundations builds the software that manages OpenAI’s GPU compute infrastructure across sites, data centers, and infrastructure providers, supporting model training and inference.
- kubernetes
Posting
ABOUT THE TEAM Compute Foundations builds the software that manages OpenAI’s GPU compute infrastructure across sites, data centers, and infrastructure providers, supporting model training and inference. Our systems turn large, heterogeneous fleets of machines into dependable compute for research and products. We build Kubernetes-based control planes, controllers, services, and APIs that coordinate the lifecycle of machines and clusters. We connect global infrastructure management with the realities of bare-metal systems, giving clients consistent interfaces across differences in hardware, topology, and provider behavior. ABOUT THE ROLE You will build distributed systems that provision, configure, and manage compute throughout its lifecycle. Your work will connect global services and Kubernetes controllers with the systems that bring machines online, update them safely, and recover them when something goes wrong. This role combines software architecture with an understanding of how machines and data centers work. You might design a lifecycle API, improve controller performance under high concurrency and provider rate limits, or trace a provisioning failure from an API through reconciliation to network boot or host configuration. You will help these systems remain reliable as the fleet expands across sites and generations of GPU hardware. We value depth in relevant systems and the ability to connect layers. You do not need to arrive as an expert in every component of the stack. IN THIS ROLE, YOU WILL: - Design, build, and operate Kubernetes-based controllers and distributed services that coordinate infrastructure across sites, isolate failures, and scale as GPU capacity grows. - Define APIs and resource models that let clients request and track lifecycle operations through consistent interfaces across hardware platforms and providers. - Build provisioning and configuration services that coordinate network boot, hardware management interfaces, and the deployment of firmware, operating-system images, drivers, and host configuration. - Develop lifecycle management for discovery, allocation, provisioning, upgrades, maintenance, recovery, and decommissioning, integrating with health and validation systems. - Design reliable reconciliation and recovery through concurrent changes, interrupted operations, and partial failures, with staged rollouts that limit disruption across nodes, racks, and clusters. - Improve control-plane throughput, AP