Physician reviewing clinical EHR vignettes and reasoning to evaluate medical AI systems. Flexible, project-based work fitting around clinical practice.
Responsibilities
Evaluate clinical EHR vignettes paired with questions, proposed answers, and distractor trap answers across diagnosis and treatment tasks
Score vignette accuracy and completeness, whether the vignette gives away the answer, answer correctness and gradeability, and trap quality
Check whether reasoning chains reach answers from vignette facts alone
Correct reasoning traces and write short rationales
Participate in three independent blind reads followed by physician adjudication
Complete project tasks within the project timeline and listed acceptance criteria
Follow the workflow: apply, pass qualification(s), join a project, complete tasks, and get paid
Requirements
Medical degree (MD or DO)
Actively practicing physician living outside the US
Active, unrestricted US medical license, verified at onboarding and re-checked monthly
Board certification or completed residency training
Recent direct patient care; attending-level preferred
Broad, multi-system diagnostic and treatment experience in internal, family, emergency, or hospital medicine
Strong clinical reasoning, including differential diagnosis, next-step management, and application of evidence-based guidelines
Strong written English (C1+)
CV submitted in English and English proficiency level indicated
Not suitable for medical students, unlicensed medical graduates, non-physician clinicians, or non-clinical healthcare titles
Benefits
Paid per approved task at about $100/hr equivalent, with one flat rate for every approved task
Flexible contribution schedule; choose when and how much to contribute
Contribute anytime, from anywhere
No patient contact and no malpractice exposure
$50 one-time onboarding reward, paid once the first production task is approved
Incentives: additional earnings for high-quality approved tasks
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US - licensed physicians evaluating clinical EHR vignettes for Mindrift’s medical AI projects. Scoring clinical reasoning, answers, traps, and evidence - based treatment quality.