Internal Medicine Physician (MD/DO)

Turing•San Francisco, CA
•Remote

About The Position

In this project, the Internal Medicine Physician will apply their expertise in internal medicine to help fine-tune large language models. The role focuses on ensuring AI systems produce accurate, empathetic, and safe medical reasoning through expert contributions grounded in diagnostic reasoning, chronic disease management, and patient care. The physician will develop and solve advanced clinical scenarios, evaluate AI-generated responses, identify gaps in models’ understanding across internal medicine subspecialties, and provide structured feedback. The role involves collaboration with AI researchers and medical peers to improve model quality and reliability for clinical and educational applications. This is a fully remote contractor/freelancer engagement requiring 20–40 hours per week, a minimum of four hours per day, and some overlap with Pacific time. The initial duration is one month, with a possible extension. The role does not include medical or paid leave.

Requirements

  • MD or equivalent degree.
  • Active practice within the last three or more years.
  • Board certification or equivalent qualification in Internal Medicine.
  • Strong understanding of the full spectrum of internal medicine, including acute care, chronic disease, and preventive medicine.
  • Ability to explain complex medical reasoning clearly in patient-friendly language.
  • Excellent written and spoken English.

Nice To Haves

  • Familiarity with digital medical tools.
  • Education from a top-tier institution, such as Harvard, Stanford, UCSF, or Oxford.

Responsibilities

  • Design and solve advanced clinical scenarios reflecting internal medicine practice, including complex differential diagnoses and chronic care management.
  • Evaluate AI-generated responses for diagnostic accuracy, clinical judgment, and evidence-based reasoning.
  • Identify gaps in AI understanding across internal medicine subspecialties.
  • Collaborate with AI researchers and medical peers to improve model quality and reliability.
  • Provide structured expert feedback to inform AI development for clinical and educational applications.
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