Role Overview In this project, you will leverage your expertise in internal medicine to help fine-tune large language models (like ChatGPT). Your deep understanding of diagnostic reasoning, chronic disease management, and patient care will help ensure AI systems deliver accurate, empathetic, and safe medical reasoning.

What You’ll Do Design and solve advanced clinical scenarios reflecting internal medicine practice, from complex differential diagnoses to 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 that informs next-generation AI development for clinical and educational applications.

Candidate Requirements MD or equivalent; active practice within the last 3+ years. Board certification or equivalent qualification in Internal Medicine. Strong grasp of internal medicine’s full spectrum — acute care, chronic disease, and preventive medicine. Skilled in articulating complex medical reasoning in clear, patient-friendly language. Excellent written and spoken English; familiarity with digital medical tools is a plus. Education from a top-tier institution (e.g., Harvard, Stanford, UCSF, Oxford, etc.).

Offer Details Commitment: 20–40 hours/week (minimum 4 hours/day, with overlap in PST) Engagement: Contractor/freelancer (no medical or paid leave) Duration: 1 month, with possible extension Remote: Fully remote, collaborative environment

About Turing Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.

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