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About the Role
Drive research agenda towards advancing AI model capabilities on real-world healthcare tasks. Build novel datasets, environments, and benchmarks to identify capability gaps in current models, publish academic papers, and post-train models to push the SOTA while staying grounded to the demonstrated needs of our healthcare partners.
Responsibilities
- Drive research agenda towards advancing AI model capabilities on real-world healthcare tasks.
- Build novel datasets, environments, and benchmarks to identify capability gaps in current models.
- Publish academic papers.
- Post-train models to push the SOTA while staying grounded to the demonstrated needs of our healthcare partners.
Requirements
- A medical degree (PA, RN, NP, MD, DO, etc.).
- Willing to work in-person, full-time in San Francisco.
- Intermediate software engineering skills and programming proficiency (i.e. not just Claude Code) in Python and Javascript.
Skills
- Foundational knowledge in medicine and clinical training
- Experience working in a live clinical setting
- Understanding of healthcare data standards (e.g., EHR data structures, interoperability, HIPAA considerations)
- Strong interest in AI and machine learning applications
- Experience with clinical workflow analysis, quality improvement initiatives, or digital health product development
- Prior track record of publishing academic research
Location
- San Francisco
Work Type
- In-person
- Full-time
Education Level
- Medical degree (PA, RN, NP, MD, DO, etc.)
Benefits
- Competitive compensation
- Meaningful equity
- Unlimited PTO
- Comprehensive health, dental, and vision coverage
- 401(k)
- Free lunch + dinner
About the Company
- Kinetic Systems is a Stanford PhD spinout whose mission is to advance the capabilities of frontier AI models for solving clinically and economically meaningful healthcare tasks.
- Founded in 2025 and are backed by General Catalyst.