San Francisco
8 months ago

Job Overview

Job Type
FullTime
Pay
Not disclosed

Job description

Location:
San Francisco, United States
Work arrangement:
On-site

Role Summary

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.

Responsibilities

  • 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

Requirements

  • 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)

About the Company

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
Role:
Member of Technical Staff - Research Scientist
Job Type:
FullTime

Company profile

kineticsystems

kineticsystems.ai

Kinetic Systems is an applied AI research lab focused on improving frontier models to solve clinically and economically meaningful healthcare tasks, working toward autonomous healthcare. It shares benchmarks, papers and writing on AI agents for real-world healthcare environments that its team has contributed to, such as HealthAdminBench and MEDS, an emerging data standard and ecosystem for health AI. The lab offers new hires founding-level impact and ownership.

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