Remote Resident Physician (MD/DO) - 42012

Turing; Denver (CO); À distance; USD 207 000 - 344 000; Temps partiel

Résumé du poste

A leading AI research accelerator is seeking an experienced medical professional to enhance AI systems through your expertise in emergency and internal medicine. Responsibilities include designing clinical scenarios, evaluating AI responses, and working with researchers to improve model reliability. This fully remote contractor role requires an MD with active practice experience and strong diagnostic skills. Join a collaborative team to influence the next generation of AI in healthcare.

Qualifications

• Active practice in internal or emergency medicine within the last 3+ years.
• Board certified in Internal or Emergency Medicine.
• Strong understanding of acute care, chronic disease, and preventive medicine.
• Experience in articulating complex medical reasoning to non-specialists.
• Fluency in English; familiarity with digital medical tools is a plus.
• Education from a top-tier institution (e.g., Harvard, Stanford, UCSF, Oxford, etc.).

Responsabilités

• Design advanced clinical scenarios for AI model training.
• Evaluate AI responses for accuracy and clinical judgment.
• Identify gaps in AI understanding of medical subspecialties.
• Collaborate with AI researchers to enhance model quality.
• Provide expert feedback for AI development in medical applications.

Connaissances

Diagnostic reasoning

Chronic disease management

Patient care

Clear communication

Digital medical tools

Formation

MD or equivalent

Education from a top-tier institution

Training at top-tier institution

Outils

Digital medical tools

Description du poste

Role Overview

In this project, you will leverage your expertise in internal or emergency 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 or emergency 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 (cardiology, endocrinology, nephrology, etc.).
• 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 or Emergency 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.).

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, drive lasting results on the P&L.

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