
Licensed Physician – Freelance AI Trainer
Posted 3 days ago

Posted 3 days ago
This is a fully remote position, open to applicants in United States.
• Assess clinical EHR vignettes along with associated questions, suggested answers, and misleading “trap” answers related to diagnosis and treatment tasks.
• Analyze cases that cover cardiovascular, nervous, hematologic, respiratory, digestive, urinary, reproductive, musculoskeletal, and integumentary systems.
• Evaluate the quality of clinical reasoning, accuracy and completeness of vignettes, correctness and gradeability of answers, as well as the quality of trap answers.
• Determine if reasoning chains derive conclusions solely from the facts presented in the vignettes.
• Amend reasoning paths and create concise rationales.
• Collaborate within three independent blind evaluations followed by physician adjudication.
• Complete tasks by specified deadlines and adhere to outlined acceptance criteria.
• Must be a US-based, actively practicing physician with an MD or DO degree.
• Hold an active, unrestricted US medical license, verified by the issuing medical board.
• Must have board certification or completed residency training.
• Recent experience in direct patient care is required; attending-level experience is preferred.
• Possess extensive multi-system diagnostic and treatment experience in internal, family, emergency, or hospital medicine.
• Strong clinical reasoning skills, including differential diagnosis, next-step management, and the application of evidence-based guidelines are essential.
• Proficient written English at a C1+ level.
• CV must be submitted in English.
• Previous experience in medical AI evaluation, clinical content or exam-question review, or medical annotation/QA is advantageous.
• Applicants must not be medical students, unlicensed medical graduates, non-physician clinicians, or non-clinical healthcare professionals.
• Compensation is provided per accepted task.
• Competitive rate up to the equivalent of $60/hr, contingent on qualification tier and task efficiency.
• Opportunities for part-time, project-based work.
• Flexible workload averaging approximately 10–20 hours per week during active project phases.
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