Real world training envs for healthcare AI models. Backed by Y Combinator.
About the role
As an RL Engineer at BioStack, you will build reinforcement learning environments and post-training systems for healthcare AI. BioStack is building the data and environment layer for medical AI: sourcing high-value clinical data, turning it into model-ready workflows, and building tasks, rewards, verifiers, benchmarks, and agent environments where models can learn against meaningful and measurable outcomes.
What they're looking for
- 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
More about this role
BioStack is building the data layer for AI-native healthcare and drug discovery. We work with leading AI labs, human data companies, and frontier biotech teams to source, structure, and deliver high-value clinical and preclinical datasets for model training, evaluation, and deployment.
We sit at the intersection of healthcare, frontier AI, and data infrastructure. Our work spans medical institutions, clinics, imaging centers, and data partners globally, turning messy real-world clinical workflows into AI-ready products that matter.
The long-term vision is to make high-quality healthcare accessible to everyone and radically improve drug discovery by linking real-world healthcare data with genomics, imaging, biomarkers, and experimental data. This creates a foundation for AI systems that can learn from millions of patient journeys, understand why treatments work for some patients and fail for others, personalize care based on clinical and genomic context, identify the right interventions earlier, and uncover new therapeutic opportunities from the connection between biology and real-world outcomes.
BioStack is backed by PeakXV, Y Combinator, Afore Capital, SV Angel as well as...
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