OpenAI· Research· San Francisco
Research Infrastructure Engineer, Training Systems
Comp$295K – $380K
Classified Tasks (11)
Automate 0%Augment 100%Human-Only 0%
Augment (11)
AI assists, human decides
Build and maintain infrastructure for large-scale model training and experimentation
technical
Design APIs and interfaces that make complex training workflows easier to express and harder to misuse
technical
Improve reliability across training and data pipelines
operational
Improve debuggability across training and data pipelines
operational
Improve performance across training and data pipelines
technical
Debug issues spanning Python, PyTorch, distributed systems, GPUs, networking, and storage
technical
Write tests, benchmarks, and diagnostics that catch meaningful regressions
technical
Turn novel research ideas into runnable, measurable training workloads for large models
technical
Build tools, abstractions, and runtimes to enable experiments that are too slow, brittle, or difficult to express
technical
Make new training approaches practical at scale by building necessary infrastructure
technical
Debug using profiles, traces, logs, tests, and minimal reproductions
technical
Job description
Research Infrastructure Engineer, Training Systems | OpenAI Careers ## Research Infrastructure Engineer, Training Systems Research - San Francisco Apply now(opens in a new window) **About The Team** The team works on research and systems that advance frontier models. Our work often goes beyond standard training recipes, which means we also build the infrastructure needed to make new training approaches practical at scale. This is a team where systems work is directly tied to research progress: better tools, abstractions, and runtimes can unlock experiments that would otherwise be too slow, brittle, or difficult to express. **About The Role** This is a systems engineering role focused on ML training infrastructure. You will work on the systems layer that turns novel research ideas into runnable, measurable training workloads for large models. The work can sit on the critical path for model releases, bringing both the excitement of direct impact and the responsibility of building systems that remain reliable under real pressure. **In This Role, You Will** * Build and maintain infrastructure for large-scale model training and experimentation. * Design APIs and interfaces that make complex training workflows easier to express and harder to misuse. * Improve reliability, debuggability, and performance across training and data pipelines. * Debug issues spanning Python, PyTorch, distributed systems, GPUs, networking, and storage. * Write tests, benchmarks, and diagnostics that catch meaningful regressions. **You Might Thrive In This Role If You** * You want to build systems that enable new model training approaches, not just optimize established ones. * You have strong systems instincts and care deeply about performance, reliability, and clean abstractions. * You have good taste in API and interface design, with empathy for the researchers and engineers using your tools. * You are comfortable working across ML research code and production-quality infrastructure. * You enjoy debugging from evidence: profiles, traces, logs, tests, and minimal reproductions. **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