Global Medical Expert Network (Pathology, Radiology, Cardiology)

Role Overview

You will bring your medical judgement to the front line of AI development, reviewing clinical images and annotations to ensure the models learn from accurate, expert-level data. Day‑to‑day work involves validating diagnostic labels, flagging inconsistencies, and advising engineering teams on clinical nuance. This role is critical because even small errors in training data can cascade into inaccurate AI outputs, and your expertise directly safeguards the reliability of tools used in real patient care.

Key Responsibilities

• Review and validate medical imaging datasets (e.g., pathology slides, radiology scans, cardiology studies) for correctness and completeness.
• Provide expert feedback on model predictions, highlighting false positives or missed findings to improve diagnostic accuracy.
• Collaborate with clinical and product teams to refine annotation guidelines, ensuring they reflect real‑world practice.
• Audit training materials and quality assurance workflows, suggesting revisions to reduce labelling drift.
• Participate in calibration rounds with other clinicians to standardise interpretation across rare or ambiguous cases.
• Document edge cases and clinical reasoning to help engineers understand model limitations.
• Contribute to short‑cycle validation sprints, where rapid expert review is needed before a model release.

Requirements & Qualifications

• A recognised medical degree (MD, DO, MBBS or equivalent) – residents, fellows, and board‑certified specialists are all welcome.
• Active, previously held, or in‑progress board certification in Pathology, Radiology, or Cardiology.
• Hands‑on clinical experience in diagnostics, direct patient care, or medical education (any setting – hospital, private practice, or academic).
• Familiarity with digital health platforms, AI/ML concepts in medicine, or prior work with medical data annotation is a plus but not mandatory.
• Strong attention to detail and a commitment to ethical standards when handling patient‑derived data.
• Professional fluency in English, both written and verbal.

What We Offer / Why Join

You will join a globally diverse team that prioritises giving back and creating a sense of belonging. Projects are purpose‑driven, with the direct mission of using AI to improve healthcare outcomes worldwide. Engagement is flexible – part‑time, contract, or project‑based – so you can contribute alongside your existing clinical work. This is a rare opportunity to apply your hard‑earned medical knowledge to technology that can scale expert diagnostics to underserved populations.