Medical Quality Assurance Lead (QAL)

As a Medical Quality Assurance Lead, you will oversee quality across medical AI training projects. You will review AI-generated explanations, patient-facing responses, case analyses, diagnostic discussions, treatment summaries, medication content, and trainer or QA submissions.

You will also help keep review standards consistent across remote teams by answering clinical questions, sharing guideline updates, supporting onboarding, and improving medical QA workflows.

• Review medical AI outputs and trainer or QA work for accuracy, clinical reasoning, correct terminology, clarity, and patient-safety awareness.
• Give precise written feedback and escalate recurring or critical quality issues.
• Explain 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 training for medical review workflows.
• Identify recurring gaps and help improve scalable QA processes for medical AI training projects.

This is a part-time contractor role open to candidates in the United States. The work requires strong written English for feedback and team coordination, along with substantial medical knowledge and experience.

• Pay: $95 per hour.
• Time: 20 or more hours per week.
• Location: Open to candidates in the United States.
• Work type: Part-time contract work.
• Experience level: Intermediate.
• Education: A 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.
• Evaluation skills: Ability to assess AI-generated medical content against detailed rubrics and identify unsafe or inaccurate outputs.
• Preferred: Experience leading or supporting remote teams of trainers, reviewers, clinicians, or QAs.
• Helpful background: AI training, data annotation, prompt and response evaluation, medical content QA, or rubric-based large language model evaluation.

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

AI training is the human work of reviewing and improving examples used to build artificial intelligence, including rating model responses and checking specialized content. OpenTrain helps people find these roles, build an AI training profile, and start applications in one place.