Research Engineer - RL and Post Training

BioStack Platforms is building the data layer for AI-native healthcare and drug discovery by transforming clinical and biomedical data into AI-ready products. The Research Engineer will build reinforcement learning environments and post-training systems for healthcare AI, including designing rewards and verifiers, training and evaluating agents, running experiments, and improving data and feedback pipelines.

Responsibilities:

• Build healthcare-specific RL environments, including tasks, action spaces/tool interfaces, reward functions, verifiers, and evaluation harnesses
• Run post-training experiments on language models and agents using techniques such as SFT, RLVR, RLHF/RLAIF, and reward modeling
• Turn clinical and biomedical datasets into training environments with measurable, verifiable outcomes
• Design rewards and verifiers that capture correctness across clinical reasoning and longitudinal decision-making tasks
• Train and evaluate multi-step agents operating across patient histories, clinical tools, and structured/unstructured medical data
• Build scalable pipelines for rollouts, training, evaluation, experiment tracking, and dataset iteration
• Analyze model failures and use them to improve environments, rewards, datasets, and subsequent training runs