Member of Clinical Staff

Kinetic Systems, Inc.; San Francisco (CA); On-site; USD 120,000 - 200,000; Full time

Benefits offered by this job

Unlimited PTO

Comprehensive health, dental, and...

Job summary

Kinetic Systems in San Francisco is seeking a Member of Clinical Staff to shape AI model development for real-world healthcare tasks. You will design RL environments capturing authentic clinical work, build datasets, evaluate frontier models, publish papers, and guide data strategies with clinicians.

This is a full-time in-person SF role. You will lead initiatives that stress-test models and ensure clinical judgment is embedded in data and evaluation rubrics, advancing responsible AI for health.

Qualifications

• Must have one of the specified medical degrees (MD, DO, MBBS, NP, or PA).
• At least 2+ years of experience in a real clinical environment.
• Experience designing evals, rubrics, or leading clinical data projects at frontier AI labs or data companies.
• Experience building RL environments, evals, or graders.

Responsibilities

• Design and build RL environments that capture real clinical work.
• Identify gaps in frontier models on real clinical workflows and create evals, benchmarks.
• Stress-test environments to prevent shortcut exploitation by models.
• Write rubrics and guidelines reflecting expert clinical judgment.
• Build gold-standard datasets and pilot tasks with clinician input.
• Lead calibration with clinician raters and adjudicate hard cases.
• Collaborate with ML team to translate needs into data, publish papers.

Skills

Clinical environment experience

Healthcare data handling

Team leadership

Academic writing

Education

MD/DO/MBBS/NP/PA

Tools

RL environments design

Evaluation rubrics design

Job description

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.

The Role

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.

This is not an annotation role. You'll design the work others do. The clinical judgment you encode into our data decides whether a model gets a real clinical workflow right, or gets it confidently wrong.

Note: This is a full-time role, required to be in-person in SF.

What You'll Do

• Design and build RL environments that capture real clinical work
• Find where frontier models fall short on real clinical workflows, and turn those gaps into environments, evals, and benchmarks
• Stress-test your own environments, hunting for shortcuts and reward hacks before a model finds them
• 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 our clinician network works to
• 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

Who You Are

• 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). Not just completing tasks: you've designed evals, written the rubrics others worked from, led teams of clinical experts, or owned data that a frontier lab trained or evaluated on
• You've built RL environments, evals, or graders yourself, not just read about them
• You understand how data quality shapes model training, including preference data, rubric design, and rater agreement
• You understand healthcare data standards (e.g., EHR data structures, interoperability, HIPAA considerations)
• You have experience with clinical workflow analysis, quality improvement initiatives, or digital health product development

Why Us

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