Medical Quality Assurance Lead (QAL)

In this hourly, remote contractor role, you will work as a Medicine Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across medical AI training projects. You will review AI-generated medical content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.

You will assess work for medical accuracy, clinical reasoning quality, guideline awareness, patient-safety awareness, terminology correctness, clarity, risk sensitivity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong medical expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote medical-review teams.

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 medical quality leadership will directly help improve the world’s premier AI models by ensuring that medical training data is accurate, clinically sound, clearly explained, appropriately cautious, safety-aware, well-documented, and aligned with client expectations.

Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Requirements: - Medical degree such as MD, DO, MBBS, MBChB, or equivalent; advanced clinical, biomedical, nursing, pharmacy, or healthcare-related degrees may be considered depending on project requirements. - Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear medical-review feedback in English. - 3+ years of professional experience in medicine, clinical practice, medical research, medical education, clinical documentation, healthcare QA, medical writing, guideline review, or related workflows. - Strong understanding of core medical topics such as clinical reasoning, differential diagnosis, pathophysiology, pharmacology, diagnostics, treatment principles, patient safety, evidence-based medicine, medical terminology, and healthcare communication. - Ability to evaluate medical content against detailed rubrics and identify issues such as unsafe recommendations, hallucinated facts, missing caveats, incorrect clinical reasoning, overconfident diagnosis/treatment claims, inappropriate patient advice, or incomplete explanations. - Familiarity with medical workflows or references such as clinical guidelines, diagnostic pathways, medication safety, chart review, case summaries, patient education materials, medical literature, and evidence-based review is preferred. - Experience leading or supporting remote teams of trainers, annotators, reviewers, clinicians, medical writers, researchers, educators, or QAs is strongly preferred. - Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. - Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation. - Experience with AI training, data annotation, large language models, prompt/response evaluation, medical content QA, or rubric-based LLM evaluation is a strong plus.