Pediatric Care MD - AI Trainer

Mercor; Houston (TX); Remote; USD 138,000 - 207,000; Part time

Job summary

Mercor is seeking physicians (MD) with pediatric emergency department or pediatric urgent care experience to review, annotate, and evaluate clinical documentation for AI systems. This remote, part-time role focuses on ensuring accuracy, safety, and clinical usefulness of AI-generated outputs.

Ideal candidates hold an MD with pediatric emergency medicine background, are US-based, and can commit a minimum of 10 hours per week through mid-November. Prior AI/ML annotation experience is a plus.

Qualifications

• MD with pediatric emergency medicine or pediatric urgent care background.
• US-based physician available for remote, part-time work.
• Willingness to contribute to AI annotation and documentation reviews.

Responsibilities

• Review pediatric ED/urgent care documentation for accuracy and safety.
• Annotate clinical encounters and evaluate AI-generated summaries.
• Provide structured feedback to engineering/product teams.
• Contribute ideas to guideline development and edge-case definitions.

Skills

Pediatric Emergency Medicine

Education

MD (US)

Pediatric Emergency Medicine

Job description

Mercor is hiring physicians (MD) with pediatric emergency department or pediatric urgent care experience on behalf of a healthcare AI partner building advanced clinical documentation tools. In this role you will apply your pediatric acute-care expertise to review, annotate, and evaluate clinical documentation, directly shaping the accuracy, safety, and clinical usefulness of medical AI systems.

Key Responsibilities

Clinical Documentation Review

• Review pediatric emergency and urgent care documentation and patient charts for accuracy, completeness, and clinical soundness

• Evaluate AI-generated clinical summaries against what a practicing pediatric acute-care physician would expect to see

Annotation & Structured Feedback

• Annotate clinical encounter data against detailed guidelines

• Flag omissions, hallucinations, clinical inaccuracies, and documentation gaps in AI-generated output

• Provide structured, written feedback that engineering and product teams can act on

Knowledge Contribution

• Contribute expert input on annotation guidelines and edge-case definitions

• Raise clarifying questions where guidance is ambiguous and help refine the guidelines

Required Qualifications

• MD with a background in pediatric emergency medicine or pediatric urgent care

• US-based

• Available for a minimum of 10 hours/week through mid-November

Preferred Qualifications

• Prior AI/ML annotation or model evaluation experience (with positive performance reviews)

Work Arrangement

• Remote, part-time

• Flexible scheduling, designed around an active clinical practice