Senior Dermatology AI Evaluation Reviewer

The work

You will provide senior clinical judgment for evaluating AI model outputs and curating a longitudinal dermatology dataset. The work focuses on complex or ambiguous cases, structured reviewer consensus, and clear documentation based on current dermatology guidelines.

• Lead clinical reviews of complex or ambiguous dermatology cases.
• Resolve clinical disagreements among reviewers through structured consensus.
• Help develop clinical evaluation frameworks for assessing AI model outputs.
• Provide expert input during designated review discussions and subspecialty consultations.
• Write guideline-aligned clinical commentary and document defensible conclusions.
• Communicate reliably with peer reviewers and disclose conflicts of interest so assignments can be handled appropriately.

What it pays and takes

This is a fully remote, asynchronous independent contractor engagement with occasional synchronous calls. Compensation is paid per task, with rates based on experience, academic standing, and clinical expertise.

• Expected average workload: 15 hours per week, with up to 40 hours per week during peak batches.
• Engagement length: four weeks.
• The listing indicates a time commitment of 20 or more hours per week; the role description states an expected average of 15 hours, with higher peak-batch capacity.
• Location: United States.
• Language: English.
• Faculty appointment at the Assistant Professor level or above at an accredited US medical school or academic medical center.
• At least three years since completing residency.
• Board certification in dermatology by the American Board of Dermatology.
• Active medical license in good standing in at least one US state.
• Active clinical practice.
• Strong knowledge of current dermatology guidelines, written clinical reasoning, consensus leadership, complex clinical cases, graphic medical images, and review protocols.

Helpful background

The role is designed for academic dermatologists who want to apply senior clinical expertise to clinical AI evaluation. The following experience is helpful but not required by the listing.

• Fellowship training in dermatopathology, Mohs or procedural dermatology, pediatric dermatology, or complex medical dermatology.
• Peer-reviewed dermatology publications or journal peer review.
• IRB or research committee service.
• Teaching residents or fellows.
• Specialty-society involvement.
• Previous clinical AI, digital health, or dermatology AI research experience.

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 to help AI systems learn from examples and produce more reliable results. Experienced clinicians are needed for specialized work because they can assess difficult cases, explain their reasoning, and judge model outputs against professional standards.