[Hiring] Member of Technical Staff, Reinforcement Learning @True Talent Solutions Partners

Role Description

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.

Qualifications

• 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.

Requirements

• 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.