Dermatology Clinical AI Evaluation Expert

OpenTrain AI, Inc.; Northern (KY); Hybrid; USD 54,000 - 103,000; Part time

Benefits offered by this job

Fully remote

Job summary

OpenTrain AI, Inc. seeks a senior dermatology reviewer to provide expert clinical judgment on complex dermatology cases and evaluate longitudinal data for AI systems. You will document commentary according to guidelines and participate in consensus processes, with occasional synchronous calls.

This remote, part-time contractor role requires board-certified dermatologists with an active US license and an academic appointment (Assistant Professor or higher).

Qualifications

• Board certification in dermatology and an active US medical license.
• Academic appointment at least at Assistant Professor level.
• Fellowship training with peer-reviewed publications and leadership in dermatology.

Responsibilities

• 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.

Skills

Clinical writing

Guideline familiarity

Consensus leadership

AI evaluation

Education

Board certification in dermatology (ABMS)

Active medical license in at least one US state

Assistant Professor or higher at a US medical school/academic medical center

Subspecialty fellowship training with peer-reviewed publications

Job description

The work

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.

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.