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.
As a Member of Technical Staff (Research Engineer), you’ll help drive our research agenda towards advancing AI model capabilities for real-world healthcare tasks. You'll be joining an energetic, early-stage startup environment and have ownership across the full stack of what we do: product, research, training, evals, and infrastructure.
Note: This is a full-time role, required to be in-person in SF.
Develop novel evals, RL environments, and benchmarks to reflect real-world healthcare workflows
Develop, train, and evaluate computer-use agents for complex healthcare interfaces
Write and publish papers in academic conferences
Published at 1+ first-author papers in a top ML conference (NeurIPS, ICLR, ICML, etc.)
Have experience with PyTorch, HuggingFace, or similar libraries
Familiar with best practices around RLEs, benchmarks, evals, and post-training
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
Job details are sourced from the employer's original posting.
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Kinetic Systems is an applied research lab building data infrastructure for the autonomous hospital. They focus on advancing the capabilities of frontier models for solving clinically and economically meaningful healthcare tasks.