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.
BioStack is backed by Y Combinator, Afore Capital, SV Angel, Emerson Collective, and high-profile angels from xAI, Meta and Google DeepMind.
About the Role
As an RL Engineer at BioStack, you will help build the reinforcement learning infrastructure for healthcare AI.
BioStack is building the data engine and RL environment layer for medical AI systems. We source high-value clinical datasets, structure them into model-ready workflows, build benchmarks and reward functions, and create healthcare-specific environments where agents can learn to reason, decide, and improve against verifiable outcomes.
This role sits at the core of that effort. You will work on designing, training, evaluating, and scaling RL systems for real healthcare workflows, including clinical reasoning, chronic disease management, longitudinal patient care, medical data annotation, diagnostic decision-making, and biomedical research tasks.
We’re looking for someone with strong reinforcement learning and ML engineering experience, a bias toward fast iteration, and strong judgment around data.
The role is based in-person in San Francisco, CA. As an early team member, you’ll work closely with the founders and have the opportunity to grow into a CXO-level role.
You might thrive in this role if…
You are excited by the idea of applying frontier RL methods to healthcare, medicine, and biological data.
You have experience with reinforcement learning, language model post-training, agent environments, reward modeling, evaluation, or related ML systems.
You have strong taste in data: you can look at a dataset and quickly assess whether it is useful, noisy, biased, underpowered, poorly labeled, or capable of supporting meaningful model improvement.
You can evaluate datasets for signal quality, clinical relevance, label fidelity, longitudinal depth, coverage, edge cases, and suitability for RL environments.
You can move quickly from research concept to working prototype, then iterate based on empirical results.
You are comfortable designing controlled experiments, building baselines, and drawing trustworthy conclusions from noisy real-world data.
You like working with complex datasets, including clinical notes, labs, imaging, ECGs, longitudinal patient histories, and expert annotations.
You are comfortable working in large ML codebases and can debug training runs, data pipelines, eval harnesses, and model behavior.
You care about building systems that are technically rigorous, clinically grounded, and useful beyond demos.
You are a self-starter who can own ambiguous problems, define the right technical path, and drive projects to completion.
You thrive in a fast-moving startup environment where research, engineering, product, and customer needs all intersect.
A note for you:
You may be early in your career; just graduating, or coming in with a few internships. That is completely fine. We are a young team too.
The real question is how you are wired.
You work toward something for months, finally achieve it, and almost immediately start thinking about what comes next. You want harder problems, more responsibility, and a steeper learning curve. If that sounds like you, you will fit in here. There is no ceiling at BioStack.
We are building our own version of a small group of unconventional, relentlessly driven people who perform exceptionally when the stakes are high.
The work is technically difficult, operationally messy, and deeply consequential. We need people who want to become world-class, not merely competent.
You should want to become one of the best engineers of your generation. We will give you ambitious problems, real ownership, direct feedback, and the pressure and support to discover abilities you may not know you have.
It will be intense, demanding, and—for the right person—one of the most rewarding periods of their career.
