Senior Dermatology Clinical AI Reviewer

The Work

You will provide senior clinical judgment for the curation and evaluation of a longitudinal dermatology dataset. The work includes reviewing difficult cases, shaping evaluation methods, and advising teams that assess AI model outputs.

You will document clinically defensible decisions, help reviewers reach consensus, and follow project protocols when providing subspecialty consultation.

• Review complex or ambiguous dermatology cases.
• Resolve clinical disagreements among reviewers through a structured process.
• Help create clinical evaluation frameworks and guideline-based case commentary.
• Provide expert input on AI model outputs.
• Lead consensus across assigned batches of cases.
• Work with clinically complex cases and graphic medical images.

What It Pays and Takes

This is a remote, asynchronous independent contractor engagement with occasional synchronous calls. The engagement is scheduled for four weeks, and compensation is task-based and determined by experience, academic standing, and clinical expertise.

• Pay: Task-based compensation; the rate is determined by experience, academic standing, and clinical expertise.
• Schedule: An expected average of 15 hours per week, with up to 40 hours during peak batches. The listing also specifies a 20+ hour weekly time requirement.
• Location: United States; fully remote.
• Language: English.
• Required: Assistant Professor rank or above at an accredited US medical school or academic medical center.
• Required: American Board of Dermatology certification, at least three years of experience after residency, an active clinical practice, and an active medical license in good standing in at least one US state.
• Required: Strong written clinical reasoning, current dermatology guideline knowledge, the ability to document clinical consensus, and comfort reviewing graphic medical images.
• Helpful: Fellowship training in dermatopathology, Mohs or procedural dermatology, pediatric dermatology, or complex medical dermatology.
• Helpful: Peer-reviewed publications, journal peer review, IRB or research committee service, resident or fellow teaching, dermatology society involvement, or experience with clinical AI, digital health, or dermatology AI research.

How It Works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI Training Work

AI training is the human work behind systems that learn from examples, including reviewing clinical cases and rating model responses. OpenTrain helps people find and build careers in this field by creating a profile, showing relevant experience, and applying to projects in one place.