Research Scientist, Reinforcement Learning

We're training foundation models to natively interact with symbolic world models. As an RL Post-Training Researcher, you'll take foundation models and scale their reasoning capabilities: applying RLVR to new domains using verified rewards from the Lean kernel, pushing the frontier of autoformalization and proving, and innovating on RL algorithms, data, and evals. Your work will also define how our models leverage test-time compute to solve long-horizon logical tasks.