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Greater London, England, United Kingdom
Hybrid
Training Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We build robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, accelerating progress towards AGI.
Within Training Runtime, the Runtime Foundations team develops the distributed OS responsible for orchestrating the large numbers of processes that make up modern training workloads and providing all necessary observability and resilience to operate in frontier scale environments. Our runtime sits beneath training frameworks and on top of research infrastructure, ensuring jobs run reliably across massive clusters while maintaining performance, stability, and observability.
Success for us is measured by both system reliability and researcher velocity - enabling ideas to scale from experiments to production training runs.
As a Training Runtime: Runtime Foundations Engineer, you will work on the software that ties thousands of computers together and exposes them as a unified system.
This system has to serve individual researchers running multiple parallel experiments, as well as our largest training runs spanning 100’s of thousands and even millions of machines and accelerators. This requires easy to use, introspectable systems that can promote a fast debugging and development cycle, as well as relentless optimization for scale while maintaining stability and performance throughout.
You will work primarily in Codex + Rust, building high-performance asynchronous systems with a strong emphasis on performance, correctness, resilience, and scalability.
Working at this scale and at the frontier of AI development poses novel challenges. We support many different types of research, and the problems you will be working on are highly ambiguous and require a superb ability to jump into novel domains, understand user problems, and demonstrate both strong design judgment and proficient execution to advance our programs.
We’re looking for people who love optimizing an end-to-end platform, understanding high-performance architectures to maximize both local and distributed performance across our supercomputers. We’re looking for engineers excited by the rapid pace of responding to the dynamic and evolving needs of our training runtime and compute stack.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
Work across our Python and Rust stack
Design, build, and maintain software to orchestrate and monitor machine learning workloads on our largest supercomputers
Profile and optimize our software stack to support computation orchestration at frontier scale
Improve reliability, observability, and fault tolerance for long-running jobs
Debug complex distributed systems issues across large clusters
Respond to the changing shapes and needs of the ML systems to enable our researchers
Have experience developing distributed systems
Enjoy understanding how large systems behave and fail at scale
Love being both a developer and an operator
Care deeply about performance, correctness, and reliability
Have strong software engineering skills and are proficient in Rust or another systems programming language (e.g. C++)
Have solid Linux knowledge, and are comfortable with systems-level debugging, performance analysis, and memory profiling
Are comfortable and experienced in developing asynchronous and concurrent systems
Like high-ownership environments with light process and strong engineering agency
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.
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