Physician AI Trainer (Hospital Medicine)

You will review inpatient medical records and clinical documentation used to train AI systems. The work focuses on whether clinical information is supported by the record, where documentation is incomplete or inconsistent, and how clinical reasoning can be assessed accurately.

You will apply adult inpatient expertise across FHIR data, clinical notes, and other raw medical record information. Your feedback should be clear, precise, and consistent with the written review guidelines.

• Review FHIR data, clinical notes, and other inpatient medical record information.
• Assess clinical claims against the underlying medical record.
• Evaluate HPI, past medical history, medication reconciliation, social history, assessments, and plans.
• Identify renal- and hepatic-adjusted dosing issues, medication interactions, and age-appropriate clinical details.
• Review documentation across admissions, daily progress notes, transitions of care, and discharge workflows.
• Give feedback on clinical accuracy, completeness, and consistency.

This is a part-time contractor role open to candidates in the United States. Professional fluency in English is required.

• $80 to $125 per hour equivalent, paid per task that meets the project specifications.
• Part-time contractor work.
• Open to candidates in the United States.
• Professional fluency in English.
• MD or DO degree.
• Board certification in Internal Medicine or an Internal Medicine hospital medicine focused practice designation.
• At least five years of hospitalist experience.
• Current or recent inpatient hospitalist practice within the last two years.
• Strong understanding of adult inpatient documentation and hospital workflows.
• Comfort reviewing clinical notes and raw medical record data.
• Careful application of written review guidelines.

Experience with chart review, clinical documentation improvement, utilization review, medical coding, or clinical quality assurance is helpful. Familiarity with medication safety considerations and evaluating support for clinical claims is also valuable.

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

AI training is the human work behind systems that learn from examples, including reviewing records, rating model outputs, and checking whether information is accurate and well supported. OpenTrain is where people find AI training and data-labeling projects, build a profile, and apply in minutes, while specialist expertise can qualify contributors for higher-paid work.