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Remote Medical General Expert AI Trainer
Remote Medical General Expert AI TrainerSuperAnnotate • Ann Arbor, Michigan, US
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Remote Medical General Expert AI Trainer

Remote Medical General Expert AI Trainer

SuperAnnotate • Ann Arbor, Michigan, US
[job_card.1_day_ago]
[job_preview.job_type]
  • [job_card.full_time]
  • [filters.remote]
[job_card.job_description]

In this hourly, remote contractor role, you will review AI-generated medical responses and / or generate expert healthcare content, evaluating reasoning quality and step-by-step clinical problem-solving while providing precise written feedback. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in clinical methodology or 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 SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, 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.

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.

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.
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