You will provide senior clinical review for complex or unclear dermatology cases and help evaluate longitudinal dermatology data for AI systems. The work combines clinical judgment, guideline-based documentation, structured reviewer consensus, and expert review of model outputs.
You will work asynchronously with clinical reviewers and join occasional synchronous calls. The engagement covers assigned dermatology case batches over four weeks.
- Review complex or ambiguous dermatology cases.
- Resolve clinical disagreements through a structured consensus process.
- Help develop clinical evaluation frameworks for dermatology AI work.
- Provide expert advice on AI model outputs.
- Write clinically defensible, guideline-aligned commentary and document consensus.
- Provide subspecialty consultation when appropriate.
- Work with graphic medical images and other complex clinical material.
- Follow assigned protocols and disclose potential conflicts of interest.
What it pays and takes
This is a remote, part-time independent contractor engagement. Compensation is paid per task, with the amount determined by experience, academic standing, and clinical expertise.
- Pay: Per task; the input does not specify a rate.
- Time: 20 or more hours per week.
- Engagement: Four weeks.
- Work arrangement: Fully remote and mainly asynchronous, with occasional synchronous calls.
- Location: Open to candidates in the United States.
- Academic appointment: Assistant Professor or above at an accredited US medical school or academic medical center.
- Certification: Board certification in dermatology from the American Board of Dermatology.
- Clinical experience: At least three years of experience after completing residency.
- Practice and licensing: An active clinical practice and an active medical license in good standing in at least one US state.
- Required expertise: Subspecialty fellowship training, a peer-reviewed dermatology publication record, strong clinical writing, familiarity with current dermatology guidelines, and the ability to lead and document clinical consensus.
- Helpful background: Clinical AI evaluation, digital health, dermatology AI research, journal peer review, research committee service, teaching residents or fellows, 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 uses expert human judgment to prepare data and assess how well AI systems perform. Clinical specialists are needed to review difficult cases, explain sound decisions, and help make model outputs safer and more accurate.