Member of Technical Staff, Reinforcement Learning

ABOUT THE ROLE Join a healthtech team building clinical decision-support systems for use in public healthcare. You will own reinforcement learning environments and evaluations that help make model behavior more reliable in clinical settings. 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 task design, data creation, environment implementation, evaluation, and delivery to model-training teams. - Run post-training and agent evaluation experiments, then use failures to improve environments. - Collaborate with researchers and clinicians to validate model outputs and guide the work. WHAT WE'RE LOOKING FOR - A PhD in computer science, machine learning, or a related field, or at least three years of full-time reinforcement learning research or post-training experience. - At least three years of research or industry experience, or current status as a final-year PhD student or postdoctoral researcher. - Hands-on experience building reinforcement learning environments for post-training or agent evaluation. - Production-level Python, PyTorch, and Transformers experience, with familiarity in LLMs, reward modeling, and evaluation. - Experience owning reward functions, grading rubrics, or LLM-judge calibration, and communicating failed experiments and uncertainty clearly. - Clinical AI experience is helpful, especially in clinical reasoning, longitudinal records, or medical workflows. Knowledge of information retrieval design, constraint solving, SAT/SMT, or domain-specific languages is also useful. - Comfort working across disciplines, validating plausible model outputs, and attending in-person offsites multiple times per year. - Authorization to work remotely in Canada or the United States is required. COMPENSATION & BENEFITS Base salary range: $250,000 to $400,000 USD annually. Visa sponsorship is not available. LOCATION Remote, with the primary location in Canada. Candidates may also be based remotely in the United States.