Member of Clinical Staff

Kinetic Systems is an applied research lab building data infrastructure for the autonomous hospital. We spun out of the Stanford PhD program in 2025 and are backed by General Catalyst. Our mission is to advance the capabilities of frontier models for solving clinically and economically meaningful healthcare tasks.

The Role

As a Member of Clinical Staff, you’ll help drive our research agenda towards advancing AI model capabilities on real-world healthcare tasks. You will build reinforcement learning environments, novel datasets and benchmarks, publish academic papers, and post-train models to push the SOTA while staying grounded in the demonstrated needs of our healthcare partners.

The clinical judgment you encode into our data decides whether a model gets a real clinical workflow right, or gets it confidently wrong.

Note: This is a full-time role, required to be in-person in SF.

What You’ll Do

• Design and build RL environments that capture real clinical work

• Find where frontier models fall short on real clinical workflows, and turn those gaps into environments, evals, and benchmarks

• Stress-test your own environments, hunting for shortcuts and reward hacks before a model finds them

• Write the rubrics and guidelines that capture expert clinical judgment, especially where the right answer is subjective or high-stakes

• Build gold-standard datasets, pilot new tasks yourself, and set the quality bar our clinician network works to

• Lead calibration with clinician raters and adjudicate the hardest cases

• Work with our ML team to turn training and evaluation needs into high-quality clinical data

• Write and publish papers in academic conferences

Who You Are

• Must have one of the following medical degrees: MD, DO, MBBS, NP, or PA

• 2+ years of experience working in a real clinical environment

• You’ve done serious work in the human data space, at a frontier AI lab or a human data company (e.g., Scale AI, Surge AI, Mercor, Handshake AI, Turing). Not just completing tasks: you’ve designed evals, written the rubrics others worked from, led teams of clinical experts, or owned data that a frontier lab trained or evaluated on

• You’ve built RL environments, evals, or graders yourself, not just read about them

• You understand how data quality shapes model training, including preference data, rubric design, and rater agreement

• You understand healthcare data standards (e.g., EHR data structures, interoperability, HIPAA considerations)

• You’re comfortable working in Python: you can read and modify environment and grader code, write scripts to build and analyze datasets, and dig into model outputs yourself. AI coding tools are welcome; you understand the code they produce well enough to debug and defend it

• You work in Git alongside engineers (branches, PRs, code review)

NICE TO HAVE

• JavaScript/TypeScript, CI/CD, or AWS experience

• Experience shipping production software or digital health products

• Experience with clinical workflow analysis or quality improvement initiatives

Why Us

If you join our team, you will be joining a team with...

• Founding-level impact and ownership

• An opportunity to advance AI research in one of its most meaningful application areas

• Competitive compensation and meaningful equity

• Unlimited PTO

• Comprehensive health, dental, and vision coverage

• 401(k)

• Free lunch + dinner