Applied Research Scientist

Key responsibilities: Develop improvement loops that operate within strict data boundaries, from trace selection to deployed updates Build agents with explicit permissions and evidence trails, ensuring compliance with real procedures Conduct experiments to evaluate the impact of privacy and infrastructure constraints on learning outcomes

Required qualifications: Experience in RL/post-training, private ML systems, or regulated-domain ML Hands-on experience in building and debugging model-training or evaluation systems Strong Python skills and ability to create artifacts for research and engineering collaboration Demonstrated experimental judgment with a focus on meaningful baselines and failure attribution Evidence of exceptional work through publications, open-source contributions, or shipped products