Physician Reviewer (MD/DO) - Medical AI Evaluation

November 3, 2026

About The Company Paid per approved task, about $35/hr equivalent. One flat rate for every approved task. Built to fit around a clinical practice: <ul><li>Tasks estimated at about 10-20 hrs/week while the project is active; you choose when and how much to contribute</li><li>Contribute anytime, from anywhere</li><li>No patient contact, no malpractice exposure: you review written clinical cases</li><li>All reviewers are license-verified physicians</li><li>$50 one-time onboarding reward, paid once your first production task is approved </li></ul>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based. What This Opportunity Involves We're looking for actively practicing, US-licensed physicians (MD/DO) living outside the US, with an active, unrestricted US medical license, to evaluate clinical EHR vignettes for a medical AI evaluation project. General and internal medicine are the main focus. On this project, contributors may: <ul><li>Evaluate clinical EHR vignettes paired with a question, a proposed answer, and a distractor "trap" answer across diagnosis and treatment tasks, spanning cardiovascular, nervous, hematologic, respiratory, digestive, urinary, reproductive, musculoskeletal, and integumentary systems;</li><li>Score the clinical reasoning quality of benchmark items: vignette accuracy and completeness, whether the vignette gives the answer away, answer correctness and gradeability, and trap quality;</li><li>Check whether the reasoning chain reaches the answer from vignette facts alone, correct reasoning traces, and write short rationales;</li><li>Work within three independent blind reads, followed by physician adjudication. Real clinical complexity only. You're improving the AI tools you'll eventually use yourself </li></ul>If you're a practicing physician ready to take on this challenging and engaging project, apply to take part! What We Look For This opportunity is a good fit for US-licensed physicians living outside the US who are looking for a flexible, time-limited project they can fit around clinical practice. Ideally, contributors will have: <ul><li>Medical degree (MD or DO) and an active, unrestricted US medical license (verified at onboarding and re-checked monthly);</li><li>Board certification or completed residency training, with recent direct patient care (attending-level preferred);</li><li>Broad, multi-system diagnostic and treatment experience (internal, family, emergency, or hospital medicine);</li><li>Strong clinical reasoning: differential diagnosis, next-step management, and application of evidence-based guidelines;</li><li>Prior experience in medical AI evaluation, clinical content or exam-question review, or medical annotation/QA (a plus);</li><li>Strong written English (C1+) </li></ul>This opportunity is not suitable for medical students, unlicensed medical graduates, non-physician clinicians (NPs, PAs, nurses, pharmacists), or non-clinical healthcare titles. How It Works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid How To Apply Please submit your CV in English and indicate your level of English proficiency. Project time expectations You decide when and how much to contribute. For this project, tasks are estimated at around 10-20 hours per week during active phases. This is an estimate, not a minimum or a guaranteed workload, and applies only while the project is active. Tasks are submitted within the project timeline and need to meet the listed acceptance criteria to be approved. Earnings Earnings are per approved task, at a flat rate set to about $35/hr equivalent based on estimated task time. There are no tiers or speed adjustments to the base rate. QA and adjudication tasks are paid at a higher rate. <ul><li>$50 one-time onboarding reward, paid once your first production task is approved</li><li>Incentives: additional earnings for high-quality approved tasks. Terms are shared in the project guidelines</li></ul>

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