OpenAI · San Francisco · Hybrid

Research Scientist, Mathematical Sciences

25.9.2025

Qualifications

  • Hold a current or recent academic position in mathematical sciences (mathematics, theoretical physics, theoretical computer science) or a related field

  • Regularly use frontier models in their own research

  • Move easily between theory and code, and are eager to contribute technically as well as academically

  • Either know or are eager to learn modern AI and run AI experiments end-to-end

  • Are strong scientific communicators

  • Care about rigor and reproducibility in scientific results

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.

In this role, you will

  • Assist in designing and building frontier AI models that are great at solving frontier mathematical sciences problems

  • Build high-quality scientific datasets and synthetic data pipelines (symbolic, numeric, and simulator-based)

  • Design reinforcement and grading signals for mathematical sciences and run reinforcement learning/optimization loops to improve model reasoning

  • Define and run evals for scientific reasoning, derivations, simulations, and literature grounding; track progress over time

  • Partner with research labs and the academic community

  • Drive adoption of frontier AI within the scientific community

  • Uphold high standards for safety, data governance, and reproducibility

You might thrive in this role if you

  • Are passionate about pushing the boundaries of your field using AI

  • Have used ChatGPT to do calculations and prove or improve lemmas in your field of study

  • Communicate clearly to both scientists and AI engineers; you like collaborating across teams and with academia

Nice to have

  • Open-source contributions to mathematical science or AI tooling

  • Experience building or curating domain datasets and benchmarks

  • Experience engaging a research community (teaching, workshops, tutorials, standards)

Application

View listing at origin and apply!