Primary Care Clinical AI Evaluation Physician

The work

You will review healthcare content used in AI training and quality review. Your work will focus on primary care and general medicine scenarios involving symptoms, medical histories, clinical findings, diagnoses, and treatment decisions.

You will assess whether clinical reasoning and patient-management approaches are accurate, complete, clear, and consistent with accepted practice. You will explain your decisions with evidence-based reasoning and complete structured evaluation and annotation tasks.

• Review patient scenarios, medical histories, symptoms, and clinical findings.
• Assess differential diagnoses and appropriate next steps.
• Evaluate treatment and patient-management approaches against current clinical guidance.
• Identify incorrect, unclear, incomplete, or potentially misleading medical information.
• Provide clear feedback grounded in clinical expertise and evidence-based practice.

What it pays and takes

This is a part-time contractor role for candidates based in the United States. The listing is marked entry level, but the work requires professional experience or demonstrated expertise in primary care or a related clinical field.

• Pay: $80-$285 per hour, paid in USD.
• Time: 20+ hours per week.
• Location: United States only.
• Language: English.
• Clinical background: Primary care, family medicine, internal medicine, general medicine, or a related clinical field.
• Knowledge: Patient assessment, diagnosis, clinical reasoning, treatment planning, current clinical guidelines, and evidence-based medicine.
• Skills: Strong analysis, attention to detail, and clear written and verbal communication.
• Preferred: Relevant medical education, qualifications, or professional certifications.
• Helpful experience: Data labeling, annotation, reinforcement learning from human feedback, or AI model evaluation.

How it works

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

About AI training work

AI training work uses human reviews of examples, documents, and model responses to improve how artificial intelligence systems perform. Clinicians are paid for applying specialized medical knowledge to check whether AI-generated content is accurate, complete, and safe.