Medical AI Clinical Review Expert

You will use clinical judgment to review and improve healthcare AI training data. The work includes analyzing patient cases, clinical scenarios, healthcare data, and AI-generated medical content for accuracy, relevance, terminology, and clinical usefulness.

You will also turn complex clinical workflows and medical terms into clear guidance for model training. The role includes working with data scientists and engineers, protecting sensitive information, and following data security, privacy, and ethical requirements.

• Analyze and annotate clinical scenarios, patient cases, and healthcare data.
• Review AI-generated medical content for clinical accuracy, relevance, and correct terminology.
• Evaluate AI system outputs and identify improvements based on clinical experience.
• Explain diagnostic analysis, clinical workflows, physiology, and healthcare protocols clearly.
• Interpret electronic health records, patient data, and medical documentation.
• Work with data scientists and engineers to refine objectives and deliverables.
• Maintain high standards for data security, privacy, and ethical compliance.

This role is intended for a physician or medical professional with clinical practice experience and a strong understanding of general medicine. Experience in an AI-related role is not required.

Medical licensure and experience in internal medicine, family medicine, emergency medicine, or a related specialty are valuable for this work. Final-year residents may also be considered.

• Remote contractor work for candidates located in the United States.
• Part-time schedule of less than 20 hours per week.
• Fluent in English.
• Current or recent clinical practice experience in the United States.
• Completed medical residency; final-year residents may also be considered.
• Knowledge of diagnostic analysis, general medicine, clinical protocols, physiology, and clinical terminology.
• Strong written and verbal communication, analytical ability, and attention to detail.
• Experience interpreting electronic health records, patient data, or medical documentation.
• Medical licensure and professional experience in a general specialty or relevant subspecialty are valuable.

AI training is the human work behind systems that learn from examples, including reviewing medical content and rating model outputs. Clinical experts help make these systems more accurate, useful, and responsible in healthcare settings.