Medical AI Response Evaluator, Clinical Reviewer

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help freelancers find and grow work teaching AI systems: build a unified profile, show proof of experience, and turn AI training into a durable freelance portfolio.

OpenTrain AI is the hiring and contracting organization for this role. We bring together specialized training projects and experienced contributors who want remote, flexible work at the intersection of healthcare and AI.

AI Training Work In Medicine — Why It Matters

AI training (data labeling/annotation/human feedback) is the human side of building safe, accurate medical AI. Clinicians and health professionals annotate, review, and correct model outputs so systems learn correct reasoning, patient-safety priorities, and reliable medical facts.

This work is remote and flexible, directly shapes state-of-the-art clinical AI behavior, and is accessible to healthcare professionals who can translate their clinical judgment into clear, written feedback for models.

The Role

You will evaluate AI-generated medical responses, judge clinical reasoning, write model solutions and precise feedback, and rank multiple responses by correctness and patient safety. Your work trains and validates medical AI systems by demonstrating correct clinical methodology and factual reliability.

  • Position: Medical AI Response Evaluator (contractor, part-time)
  • Workload: 20+ hours/week (remote)
  • Pay: $90.00 USD per hour
  • Language: English (C1 or stronger)
  • Allowed countries (applicants must be resident in one listed): VN, TL, TH, SG, PK, PH, NP, MY, LK, KH, ID, BT, BD, IN, BR, DE, US
  • Data & tasks: TEXT data; label types include RLHF, EVALUATION_RATING, and TEXT_GENERATION

What You'll Do

  • Review AI-generated medical answers for accuracy, clarity, prompt adherence, and patient safety
  • Evaluate step-by-step clinical reasoning, differential diagnosis, risk stratification, and red-flag recognition
  • Fact-check clinical claims, identify unsafe assumptions, missing contraindications, dosing errors, or timeline inconsistencies
  • Write high-quality explanations and model solutions that demonstrate correct medical reasoning and clear clinical logic
  • Compare and rank multiple responses by correctness, reasoning quality, and safety; provide precise, actionable feedback
  • Contribute expert healthcare content used to train and validate medical AI behavior

Requirements

  • Medical, nursing, public-health, health sciences, or allied-health background required
  • Strong grounding in epidemiology, clinical medicine, healthcare systems, and patient care
  • Confident clinical reasoning across outpatient, emergency, and inpatient scenarios
  • Ability to evaluate differential diagnosis, risk stratification, and recognize red flags
  • Exceptional attention to detail for medical fact-checking and spotting contraindications or unsafe assumptions
  • English proficiency at C1 level or higher
  • Prior experience with AI data training, clinical documentation review, utilization review, or healthcare editorial QA is strongly preferred

Helpful Background & Work Style

Experience explaining clinical decisions clearly and precisely in writing, comfort evaluating internal consistency in timelines, physiology, and dosing logic, and a reliable self-directed work style fit this contractor role well.

This is hourly remote contractor work; you should be comfortable working independently in a structured, feedback-driven annotation workflow and delivering concise, evidence-based explanations.

How It Works — Next Steps

If you meet the requirements, apply through OpenTrain with your profile and examples of clinical writing or QA work when available. Successful applicants will be onboarded as OpenTrain contractors and given access to the annotation tasks and guidelines.

Assignments are hourly contractor shifts; compensation and scheduling are handled through OpenTrain. Building a strong OpenTrain profile helps you qualify for more medical AI projects over time.

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