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.
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
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)