The work
You will review complex and ambiguous dermatology cases in a longitudinal clinical dataset and help assess AI model outputs. The work includes expert case review, clinical consensus building, evaluation framework development, and clear written commentary.
The duties and qualifications should be reviewed before applying because the role title and subject area identify different areas of expertise.
- Lead senior-level reviews of complex or ambiguous dermatology cases.
- Resolve clinical disagreements through structured discussion and documented consensus.
- Help create clinical evaluation frameworks for AI model outputs.
- Provide expert input during model-output reviews and subspecialty consultations.
- Write guideline-aligned clinical commentary and maintain clinically defensible documentation.
- Review materials that may include graphic medical images and disclose relevant conflicts of interest.
What it pays and takes
Compensation is paid per task and is determined by experience, academic standing, and clinical expertise. This is a fully remote independent contractor role with asynchronous work and occasional synchronous calls.
- Pay: Paid per task; compensation depends on experience, academic standing, and clinical expertise.
- Workload: 20+ hours per week, with up to 40 hours during peak batches.
- Engagement: The initial engagement is planned for four weeks, and assignments may vary with project needs.
- Location: Open to candidates in the United States.
- Language: Professional fluency in English.
- Experience level: Entry level.
- Education and appointment: Faculty appointment as Assistant Professor or above at an accredited US medical school or academic medical center.
- Credentials: Board certification in dermatology by the American Board of Dermatology and an active medical license in at least one US state.
- Clinical background: At least three years after residency completion, active clinical practice, and relevant subspecialty fellowship training.
- Additional qualifications: Peer-reviewed dermatology publications, strong written clinical reasoning, familiarity with current dermatology guidelines, and the ability to lead consensus, follow protocols, and communicate constructively with expert reviewers.
- Helpful background: Clinical AI evaluation, digital health, dermatology AI research, journal peer review, IRB or research committee service, resident or fellow teaching, or work with dermatology specialty societies.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training work uses human review, written feedback, and labeled examples to help artificial intelligence systems improve. Medical experts are needed for difficult clinical cases because accurate evaluation depends on current standards, careful reasoning, and subject knowledge.