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Kinetic Systems

Member of Clinical Staff

San FranciscoOnsite · United States
Staff · FullTime · Clinical
POSTED 5 NOVVERIFIED 7H AGO
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Role
5 days opentrue age
Posted 5 Nov
Payats field
$150k–225k▲ 4.2% since first seen
▼ −11% vs market median $210k
$150k$421k
Market p25–p75
$177k–$250k
Kinetic Systems p25–p75
$199k–$421kn=3
SF Bay Area · n=789 · 365d to 6 Nov
CompanyKinetic Systems →
6open roles
Opened · 30d
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Closed · 30d
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3d of snapshots · 30d window
Market
23,259open · Staff Other
Opened · 7d
+1,6117% of open
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624,312open
All tracked boards · live 10 Nov · n=23,259
TypeScriptJavaScriptPythonAWS

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.

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.

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

HARD REQUIREMENT: 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’re comfortable working in Python: you can read and modify environment and grader code, write scripts to build and analyze datasets, and dig into model outputs yourself. AI coding tools are welcome; you understand the code they produce well enough to debug and defend it

You work in Git alongside engineers (branches, PRs, code review)

NICE TO HAVE

JavaScript/TypeScript, CI/CD, or AWS experience

Experience shipping production software or digital health products

Experience with clinical workflow analysis or quality improvement initiatives

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

401(k)

Free lunch + dinner

Source · Kinetic SystemsFirst seen 6 Nov2 editsOriginal ↗