Medical AI Quality Assurance Lead

About OpenTrain OpenTrain AI is the hiring and contracting organization for this role and the #1 platform for finding and building careers in AI training and data labeling. Create a free OpenTrain account to build your profile and apply to projects that match your expertise. Remote AI training and data-labeling opportunities A way to build experience teaching and evaluating artificial intelligence Free account creation and streamlined applications About Medical AI Training AI systems learn from examples prepared and reviewed by people with relevant expertise. In medical AI training, clinicians and healthcare specialists help evaluate explanations, case analyses, treatment information, and other model responses so systems become more accurate, clear, cautious, and useful. Work at the intersection of healthcare and cutting-edge AI Review and improve model-generated medical content Contribute to flexible, remote work in a fast-growing field The Role OpenTrain is hiring a Medical Quality Assurance Lead to oversee quality and consistency across medical AI training projects. You will review AI-generated medical explanations, patient-facing responses, case analyses, diagnostic discussions, treatment summaries, medication-related content, and trainer or QA submissions. This part-time contractor role is open to candidates in the United States and requires at least 20 hours per week. The pay rate is $95 per hour. Role: Medical Quality Assurance Lead Employment type: Contractor, part time Location eligibility: United States Time requirement: 20+ hours per week Pay: $95 per hour What You’ll Do You will combine clinical judgment with structured quality review to identify inaccurate, unclear, inconsistent, or unsafe medical content. You will also help remote trainers and QAs apply project standards consistently and improve medical review workflows. Review medical AI outputs and trainer or QA work for accuracy, clinical reasoning quality, terminology, clarity, and patient-safety awareness Provide precise written feedback and escalated recurring or critical quality issues Communicate project changes, guideline updates, and quality expectations to trainers and QAs Answer questions about clinical reasoning, guideline interpretation, evidence quality, and rubric application Maintain style guides, FAQs, trackers, examples, calibration tasks, and onboarding materials Support onboarding and training for contributors working on medical review workflows Identify recurring gaps and improve scalable QA processes for medical AI training projects Requirements This role requires substantial medical or healthcare expertise and the ability to assess AI-generated content against detailed quality and safety standards. Strong written English is essential because the work includes detailed feedback, documentation, and remote team coordination. Medical degree such as MD, DO, MBBS, MBChB, or equivalent healthcare training Strong English communication skills for written feedback and team coordination At least 3 years of experience in medicine, clinical practice, medical research, medical education, clinical documentation, healthcare QA, medical writing, guideline review, or related work Strong understanding of clinical reasoning, differential diagnosis, pharmacology, diagnostics, treatment principles, patient safety, and evidence-based medicine Ability to evaluate AI-generated medical content and identify unsafe or inaccurate outputs Medical or healthcare background with strong clinical judgment Ability to review medical content for accuracy, safety, and clarity Preferred Experience Experience coordinating contributors or working within structured review operations will help you succeed in this lead role. Familiarity with AI evaluation is valuable, but the core requirement is strong medical judgment and consistent rubric-based quality review. Experience leading or supporting remote teams of trainers, reviewers, clinicians, or QAs Familiarity with AI training or data annotation Experience with prompt and response evaluation Background in medical content QA Experience with rubric-based large language model evaluation Strong written feedback and team coordination skills #J-18808-Ljbffr OpenTrain AI