Develop high-performance asynchronous systems in Rust to optimize machine learning workloads across large supercomputers, enhancing reliability and performance of AI training processes.
Training Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We work on building robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, with the goal of accelerating progress towards AGI.
Within Training Runtime, the Process Management team develops the distributed OS responsible for launching, coordinating, and supervising the large numbers of processes that make up modern training workloads. 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: Process Management 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 Rust, building high-performance asynchronous systems with a strong emphasis on performance, correctness, and scalability.
Working at this scale and at the frontier of AI development poses novel challenges. Out-of-the-box approaches often don’t work. The problems you will be working on are highly ambiguous and require strong design judgment as well as proficient execution to advance the state of our infrastructure.
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 London, UK. 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 (not just operating them)
Enjoy understanding how large systems behave and fail at scale
Care deeply about performance, correctness, and reliability
Have strong software engineering skills and are proficient in Python and 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 working and 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.
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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