Member of Technical Staff, Reinforcement Learning

ABOUT THE ROLE Build reinforcement learning environments and evaluation systems for clinical reasoning models. This hands-on research role connects task and reward design with model training, helping create reliable decision-support tools for healthcare. WHAT YOU'LL DO - Build environments for complex clinical reasoning, including multi-step tasks, tool use, state transitions, and measurable outcomes. - Design and calibrate reward functions, grading rubrics, and LLM judges, and test them for reward hacking and misleading scores. - Own the full workflow from task design and data creation through implementation, evaluation, and delivery to model-training teams. - Run post-training and agent-evaluation experiments, using observed failures to improve environments. - Collaborate with clinicians and research leadership to validate model outputs. WHAT WE'RE LOOKING FOR - A PhD in computer science, machine learning, or a related field, or at least three years of full-time experience in reinforcement learning research or post-training. - At least three years of research or industry experience, or current final-year PhD or postdoctoral status, with a bachelor's degree or higher in a relevant technical field. - Hands-on experience building reinforcement learning environments for post-training or agent evaluation, ideally in a frontier AI lab or comparable AI organization. - Production-level Python, PyTorch, and Transformers experience, plus familiarity with LLMs, reward modeling, and evaluation. - Experience owning reward functions, grading rubrics, or LLM judge calibration, and clearly documenting failed experiments and uncertainty. - Clinical AI experience is beneficial, as is familiarity with information retrieval, constraint solving, SAT/SMT, or domain-specific languages. - Comfort collaborating across disciplines, validating plausible model outputs, working through ambiguity, and attending in-person offsites several times per year. - Must be authorized to work remotely in Canada or the United States. Visa sponsorship is not available. COMPENSATION & BENEFITS Base salary: $250,000 to $400,000 annually. Visa sponsorship is not available. LOCATION Remote, with Montreal, Quebec, Canada as the primary location. Other eligible locations include Vancouver, Canada, and remote locations in Canada or the United States.