Researcher, Training - London

OpenAI's Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture and optimization techniques, alongside long‑term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world‑class in every respect.

As a member of the training team, you will push the frontier of LLM development for OpenAI's flagship models, enhancing intelligence, efficiency, and adding new capabilities. Relevant interests may include areas such as architecture design, long‑context and efficient attention, optimization and the science of scaling. Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands‑on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck.

This role is based in London. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Design, prototype and scale up new architectures to improve model intelligence
• Execute and analyze experiments autonomously and collaboratively
• Study, debug, and optimize both model performance and computational performance
• Contribute to training and inference infrastructure

You might thrive in this role if you:

• Have experience landing contributions to major LLM training runs
• Can thoroughly evaluate and improve deep learning architectures in a self‑directed fashion
• Are motivated by safely deploying LLMs in the real world
• Are well‑versed in the state of the art transformer modifications for efficiency

This role is based in our London office, and we aren’t considering applications to work remotely at this time. We offer relocation support and follow a hybrid schedule: three days a week in the office, with the option to work from home on Thursdays and Fridays.

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. 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. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via the Internal Portal.