Medical Quality Assurance Lead

The work

You will oversee quality and consistency across medical AI training projects. Your work will focus on reviewing AI-generated medical content and trainer or QA submissions for accuracy, clear reasoning, correct terminology, patient safety, and compliance with project rubrics.

You will also help medical reviewers and trainers apply updated guidance consistently. This includes answering clinical questions, documenting standards, supporting onboarding, and improving repeatable quality checks for remote teams.

• Review medical explanations, patient-facing responses, case analyses, diagnostic discussions, treatment summaries, and medication-related content.
• Check clinical reasoning, terminology, clarity, evidence quality, and patient-safety awareness.
• Evaluate trainer and QA work against detailed rubrics and identify unsafe or inaccurate outputs.
• Give precise written feedback and escalate recurring or critical quality problems.
• Communicate project changes, guideline updates, and quality expectations to trainers and QAs.
• Answer questions about clinical reasoning, guideline interpretation, evidence quality, and rubric use.
• Maintain style guides, FAQs, trackers, examples, calibration tasks, and onboarding materials.
• Support contributor onboarding and help improve scalable QA processes for medical AI training.

What it pays and takes

This is a part-time contractor role for an intermediate-level professional. You should be comfortable reviewing detailed medical content, explaining your decisions in writing, and working with rubrics and documentation.

• Pay: $95 USD per hour.
• Time: 20 or more hours per week.
• Location: United States.
• Work arrangement: Remote, part-time contract work.
• Language: Strong written English.
• Education: Medical degree such as MD, DO, MBBS, MBChB, or equivalent healthcare training.
• Experience: At least 3 years in medicine, clinical practice, medical research, medical education, clinical documentation, healthcare QA, medical writing, guideline review, or related work.
• Knowledge: Clinical reasoning, differential diagnosis, pharmacology, diagnostics, treatment principles, patient safety, and evidence-based medicine.
• Preferred: Experience leading or supporting remote teams of trainers, reviewers, clinicians, or QAs.
• A strong plus: Experience with AI training, data annotation, prompt and response evaluation, medical content QA, or rubric-based large language model evaluation.

How it works

Apply on OpenTrain with your resume and then complete the application on the hiring site.

About AI training work

AI training uses human review to help artificial intelligence produce more accurate and useful results. Medical experts are needed to catch unsafe or incorrect answers, explain what good reasoning looks like, and help models handle health information more carefully.