Life Science Domain Expert

You will provide senior dermatology expertise for a longitudinal clinical dataset and AI model evaluation work. The role focuses on reviewing difficult cases, documenting clear clinical reasoning, and helping create consistent evaluation standards.

You will also advise on AI model outputs, write guideline-aligned case documentation, resolve disagreements among reviewers, and provide subspecialty consultation when appropriate.

• Review complex or ambiguous dermatology cases.
• Help resolve clinical disagreements through a structured process.
• Contribute to clinical evaluation frameworks and review guidance.
• Provide expert feedback on AI model outputs.
• Document clinical reasoning and reviewer consensus.
• Work with graphic medical images and clinically complex cases.

What it pays and takes

This is a fully remote, asynchronous independent contractor engagement with occasional synchronous calls. The engagement is planned for four weeks, and compensation is paid per task, with the amount based on experience, academic standing, and clinical expertise.

• Compensation: Paid per task; the amount depends on experience, academic standing, and clinical expertise.
• Schedule: 20 or more hours per week.
• Location: Open to candidates in the United States.
• Language: Professional fluency in English.
• Education and appointment: Assistant Professor faculty appointment or above at an accredited US medical school or academic medical center.
• Credentials: Board certification in dermatology and an active medical license in good standing in at least one US state.
• Experience: Active clinical practice and at least three years of post-residency experience.
• Required abilities: Strong written clinical reasoning, consensus documentation, and comfort reviewing graphic medical images and complex cases.
• Subspecialty training: Fellowship training in dermatopathology, Mohs or procedural dermatology, pediatric dermatology, or complex medical dermatology.
• Helpful background: Dermatology publications, journal peer review, IRB or research committee service, resident or fellow teaching, specialty society involvement, and familiarity with current dermatology guidelines.
• Preferred experience: Clinical AI evaluation, digital health, or dermatology AI research.
• Disclosure: Relevant conflicts of interest must be disclosed for case-assignment review.

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 artificial intelligence systems learn from accurate examples and produce better results. Clinical experts are needed for complex cases because their judgment helps evaluate model outputs and shape reliable medical tools.