Dermatologist AI Image Analyst (Non-Clinical)

Obsidian; New York (NY); On-site; USD 90,000 - 130,000; Full time

Job summary

Mercor is seeking experienced U.S. Dermatologists to contribute to AI-driven dermatology projects. This is a non-clinical, image-annotation oriented role with no direct patient care, supporting model development and evaluation.

Candidates must hold an MD with an active U.S. license and have at least 5 years of post-residency dermatology experience, plus strong clinical terminology skills and English fluency. Prior annotation or medical education experience is preferred.

Qualifications

• MD with active U.S. medical license.
• At least 5 years post-residency clinical dermatology experience.
• Experience with image annotation or medical education preferred.
• English fluency required.

Responsibilities

• Reviewing high-resolution clinical images of skin lesions and identifying dermatological conditions.
• Describing images with key medical attributes, including lesion color, shape, morphology, and distribution.
• Assessing skin health, severity, or progression from images, and evaluating how well AI-generated assessments hold up clinically.
• Writing clear guidelines and criteria that define what a high-quality dermatological assessment of an image looks like.
• Providing clinical insight to improve model understanding and classification of dermatological presentations.
• Ensuring accuracy, consistency, and adherence to medical and project standards.

Skills

Dermatology expertise

Medical license (US)

Clinical experience

Image annotation experience

English fluency

Education

MD (Medical Doctor)

Job description

Mercor is seeking experienced U.S. Dermatologists to contribute to AI-driven dermatology projects. This is a non-clinical, image-annotation oriented role with no direct patient care, supporting model development and evaluation.

Candidates must hold an MD with an active U.S. license and have at least 5 years of post-residency dermatology experience, plus strong clinical terminology skills and English fluency. Prior annotation or medical education experience is preferred.