Remote Cardiologist

Role Overview

In this project, you will leverage your expertise in cardiology to help fine-tune large language models (like ChatGPT). Your deep understanding of cardiovascular diagnostics, interventional procedures, and long-term cardiac care will help ensure AI systems deliver accurate, empathetic, and safe medical reasoning.

What You’ll Do

• Design and solve advanced clinical scenarios reflecting cardiology practice, from interpreting complex ECGs and imaging to managing heart failure and arrhythmias.
• Evaluate AI-generated responses for diagnostic accuracy, clinical judgment, and evidence-based reasoning in cardiovascular medicine.
• Identify gaps in AI understanding across cardiology subspecialties including interventional, electrophysiology, and preventive cardiology.
• 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 Cardiology.
• Strong grasp of cardiovascular medicine — coronary artery disease, heart failure, valvular disease, arrhythmias, and cardiac imaging.
• 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.