US-licensed physicians evaluating clinical EHR vignettes and reasoning quality for Mindrift’s medical AI projects. Flexible, project-based work alongside clinical practice.
Responsibilities
Evaluate clinical EHR vignettes paired with questions, proposed answers, and distractor trap answers across diagnosis and treatment tasks
Assess vignettes covering cardiovascular, nervous, hematologic, respiratory, digestive, urinary, reproductive, musculoskeletal, and integumentary systems
Score clinical reasoning quality, vignette accuracy and completeness, answer disclosure, answer correctness and gradeability, and trap quality
Verify that 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-based tasks within timelines and listed acceptance criteria
Contribute approximately 10–20 hours per week during active project phases, with flexible scheduling
Requirements
Actively practicing physician with an MD or DO medical degree
Active, unrestricted US medical license, verified at onboarding and re-checked monthly
Must be living outside the US
Board certification or completed residency training; attending-level experience preferred
Recent direct patient care experience
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+)
Prior experience in medical AI evaluation, clinical content or exam-question review, or medical annotation/QA is a plus
CV must be submitted in English with 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
Remote work; contribute anytime, from anywhere
No patient contact and no malpractice exposure
$50 one-time onboarding reward, paid once your first production task is approved
QA and adjudication tasks paid at a higher rate
Additional incentives for high-quality approved tasks
Conseiller en IA et innovation numérique pour l’Université Canadienne de Kinshasa. Formation, mentorat et accompagnement de projets numériques à distance.
French - fluent manufacturing specialist challenging language models on industrial operations, quality, automation, and safety. Documenting model errors and improving prompt engineering and evaluation metrics.
Senior ML/AI Modeler building agentic and generative AI systems for Block’s payment and financial technology brands. Automating fraud and compliance investigations at scale.
Freelance French language specialist reviewing and annotating AI outputs for naturalness, accuracy, and cultural fit. Developing alignment resources and providing linguistic QA for Meridial’s AI data project.
US - licensed physicians reviewing EHR vignettes, reasoning chains, and answers. Improving Mindrift’s medical AI systems through project - based clinical evaluation.
US - licensed physicians evaluating EHR clinical cases, reasoning, and treatment answers. Improving Mindrift’s medical AI through project - based review and adjudication.
Insurance Specialist training AI models on underwriting, claims, and risk management. Evaluating French - English insurance reasoning and documenting errors for Meridial’s AI training projects.
US - licensed physicians evaluating clinical EHR vignettes for Mindrift’s medical AI projects. Flexible, project - based work improving diagnosis and treatment AI systems.
US - licensed physicians evaluating clinical EHR vignettes and reasoning quality for Mindrift’s medical AI projects. Flexible, project - based work fitting around clinical practice.
US - licensed physicians evaluating clinical EHR vignettes for Mindrift’s medical AI projects. Scoring clinical reasoning, answers, traps, and evidence - based treatment quality.