Member of Clinical Staff
Kinetic Systems
Member of Clinical Staff
Kinetic Systems
Reinforcement learning datasets for healthcare automation
Kinetic Systems is a healthcare AI research lab. We partner with frontier labs and healthcare organizations to help make AI models safer and more reliable.
We spun out of the Stanford PhD program in 2025 and are backed by General Catalyst, Conviction, and other great investors.
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. Your clinical judgment will be encoded into models used by millions of providers and patients every day.
Note: This is a full-time role, required to be in-person in SF.
Design and build evaluations that reflect real clinical work
Find where frontier models fall short on real clinical workflows, and turn those gaps into environments, evals, and benchmarks
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 for our clinician network
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
HARD REQUIREMENT: 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)
You’ve built RL environments, evals, or graders yourself
You understand how data quality shapes model training, including preference data, rubric design, and rater agreement
You understand healthcare data (e.g., EHR data structures, interoperability, HIPAA considerations)
You’re comfortable working with code: you can read and modify environment and grader code, write scripts to build and analyze datasets, and dig into model outputs yourself
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
You work in Git alongside engineers (branches, PRs, code review)
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
Reinforcement learning datasets for healthcare automation
Kinetic Systems builds data infrastructure for autonomous healthcare delivery, providing curated reinforcement learning environments and post-training datasets for AI researchers. Its flagship HealthAdminBench benchmarks AI agents on multi-step healthcare administrative tasks such as prior authorizations, denial appeals, and ordering durable medical equipment to tune models for real-world admin work. The company differentiates itself by focusing specifically on healthcare administration economics and by applying Stanford-origin research to improve fine-tuned models for administrative tasks rather than general clinical tasks. Its goal is to help frontier AI labs, providers, MSOs, and BPOs deploy AI that can automate back-office workflows and enable more autonomous care.
Explore more opportunities at Kinetic Systems