Member of Technical Staff
Kinetic Systems
Member of Technical 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 Technical Staff (Engineering), you’ll be closely involved in all aspects of engineering, with a particular eye on building RL environments, translating research into deliverables and product, building out core infrastructure and back-end systems, and developing user-facing websites and APIs. We move at the speed of research (i.e. very fast), and you will need to as well!
Note: This is a full-time role, required to be in-person in SF.
Develop novel evals, RL environments, and rigorous benchmarks to reflect real-world healthcare workflows
Work with real healthcare data
Maintain customer-facing products
Own internal tooling (data pipelines, dashboards, observability, etc.) that helps our teams move faster
Translate research code into robust, scalable software
2+ years industry SWE experience
Strong background in React, NextJS, Tailwind, and SQL
Proficient in DevOps / CloudOps (e.g. Docker, Terraform, etc.)
Familiar with RLEs, benchmarks, evals, and post-training
Experience working with sensitive data (health, finance, etc.)
Interested in healthcare as an application (prior background not necessary)
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