Dermatology MD - AI Evaluation Specialist

Obsidian; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Mercor is hiring board-certified Dermatologists for non-clinical work developing and evaluating clinical AI systems. You will apply diagnostic expertise to image interpretation, annotation, and evaluation work that defines what a clinically sound dermatological assessment looks like.

This is a non-clinical role with no direct patient care, and you may be matched to multiple streams after onboarding based on subspecialty and availability.

Qualifications

• MD or DO with completed dermatology residency.
• Board certification or board-eligible with residency completed.
• Active, unrestricted medical license in country of practice.
• 3+ years post-residency dermatology experience, practising or previously practising.
• Written and spoken English fluency.
• Minimum 15 hours per week with adaptable scheduling.

Responsibilities

• Annotate dermatology images with structured descriptions.
• Interpret cases and provide written diagnostic reasoning.
• Grade severity and differential diagnoses from images.
• Review AI-generated assessments for clinical accuracy.

Skills

English fluency

Medical terminology

Education

MD or DO

Dermatology residency

Board certification

Job description

About the Role

Mercor is hiring board-certified Dermatologists for non-clinical work developing and evaluating clinical AI systems. You will apply your diagnostic expertise to image interpretation, annotation, and evaluation work that helps define what a clinically sound dermatological assessment looks like.

This is a non-clinical role — no direct patient care, and no responsibility for live diagnosis.

This is a shared expert pool. After onboarding you may be matched to any of several concurrent workstreams based on your subspecialty, availability, and interest. You are not committing to a single project, and you may move between streams as priorities shift.

What you may work on

Work varies by workstream and may include:

• Case interpretation with written reasoning — working through clinical cases that pair dermatological images with patient history, recording your diagnostic reasoning step by step rather than only the final impression.
• Structured image annotation — describing lesions against a defined schema: morphology, colour, configuration, distribution, and body site.
• Differential and severity assessment — recording a ranked differential with your reasoning, and grading severity or progression from images.
• Output review — judging AI-generated dermatological assessments against clinical standards, flagging hallucinated findings, missed findings, and unsupported certainty.
• Grading criteria and guideline authoring — defining what separates an excellent assessment from a merely acceptable one, so judgment can be applied consistently at scale.
• Difficult-case writing — constructing cases that probe the limits of current model reasoning, including presentations that vary across skin tones.

Task length varies by stream, from roughly 10 minutes for structured annotation up to an hour for full case authoring. You will get a specific throughput target for whichever stream you are matched to.

Required qualifications

• MD or DO with completed dermatology residency
• Board certification — ABD, or the equivalent certifying body in your jurisdiction — or board-eligible with residency complete
• Active, unrestricted medical license in your country of practice
• 3+ years post-residency clinical dermatology experience, practising or previously practising
• Strong ability to identify and describe dermatological conditions in precise medical terminology, across the full range of skin tones
• Written and spoken English fluency
• Minimum 15 hours per week, with the ability to concentrate hours when a stream is time-boxed

Preferred qualifications

• Fellowship or focused practice in dermatopathology, pediatric dermatology, surgical dermatology, or complex medical dermatology
• U.S. licensure and board certification
• Prior medical image annotation, AI evaluation, or dataset curation experience
• Teaching, rubric design, or resident assessment experience
• Published research or sustained technical writing (please link a sample)

Why this work

Dermatology is one of the most image-dependent specialties in medicine, and one where model performance still varies sharply across skin tones and rarer presentations. The reference standard these systems get graded against is written by dermatologists — here you would be writing it.