Medical General Expert

conceptual understanding; fact-check medical information; write high-quality explanations and model solutions that demonstrate correct reasoning; and rate and compare multiple responses based on correctness and reasoning quality. This role is with, a fast-growing AI Data Services company and subsidiary of, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your healthcare expertise directly helps improve the world’s premier AI models by making their clinical and public-health reasoning more accurate, reliable, and clearly explained.

Your Profile
• Bachelor’s degree (or higher) in Medicine (MD/DO), Nursing, Public Health (MPH), Health Sciences, or Allied Health, with strong grounding in Epidemiology, Clinical Medicine, Healthcare Systems, and Patient Care.
• 5+ years of professional experience in Nursing, Public Health, Health Sciences, or Allied Health.
• Confident in clinical reasoning (differential diagnosis, risk stratification, red-flag recognition) and explaining why a conclusion follows from the evidence.
• Strong understanding of disease processes, patient care concepts, public health principles, healthcare systems, and medical terminology.
• Exceptional attention to detail when fact-checking medical content and identifying unsafe assumptions, missing contraindications, or misinterpretation of tests; Minimum C1 English proficiency.
• Comfortable evaluating answers for internal consistency (timelines, physiology, dosing logic), appropriateness for setting (ED vs outpatient), and patient safety implications.
• Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones.
• Previous experience with AI data training/annotation, clinical documentation review, utilization review, or healthcare editorial QA is strongly preferred.

Key Responsibilities
• Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
• Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
• Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.