Biomedical Engineering Quality Assurance Lead

Role overview

This remote contract position is for a Biomedical Engineering Quality Assurance Lead who will guide quality control across AI training work in biomedical engineering. The role focuses on checking the accuracy, consistency, and instructional quality of biomedical content and reviewer work, then giving clear written feedback so project standards are met.

You will assess AI-produced biomedical engineering material and QA/trainer outputs against detailed project rubrics, with attention to technical correctness, biomedical reasoning, calculation accuracy, standards awareness, regulatory context, unit consistency, safety, clarity, formatting, and rule adherence. The role also includes identifying repeated issues, sharing updates with trainers and QAs, supporting onboarding, maintaining documentation, and helping re-engage contributors who are inactive.

This position sits within a fast-growing AI data services business that supports major AI companies and foundation-model labs. Your work will help improve biomedical engineering training data so that it is precise, logically sound, clearly explained, safety-conscious, and aligned with client expectations. There is no live project attached to this opening at the moment, but qualified candidates may be contacted first for future relevant opportunities through the expert network.

Key responsibilities

• Review biomedical engineering tasks regularly, identify quality gaps, and share actionable feedback with contributors and escalations when issues repeat or become serious.
• Check AI-generated explanations, medical-device reasoning, biomechanics calculations, biomaterials discussions, bioinstrumentation workflows, biosignal content, diagrams, and step-by-step solutions for accuracy and clarity.
• Keep trainers and QAs informed on workflow updates, new instructions, project changes, and biomedical-engineering-specific quality expectations.
• Answer trainer and QA queries promptly, especially where assumptions, formulas, units, biological context, device safety, standards, and rubric interpretation are involved.
• Reach out to inactive contributors, encourage participation, monitor follow-ups, and report availability concerns when required.
• Build and maintain project assets such as style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding resources.
• Lead onboarding and training sessions to explain project workflows, review standards, rubrics, and quality expectations.
• Make sure reviewers and trainers apply guidelines consistently as project requirements evolve.
• Identify unsafe, misleading, or overly confident biomedical recommendations, particularly when patient safety, clinical practice, diagnostics, imaging, rehabilitation, or regulatory claims could be affected.
• Spot recurring process issues and suggest improvements that make QA operations more scalable for biomedical engineering AI training work.

Candidate profile

• A Bachelor’s or Master’s degree in Biomedical Engineering, Bioengineering, Medical Engineering, Biomechanical Engineering, or a related field such as Electrical or Mechanical Engineering with a biomedical focus.
• At least 3 years of professional background in biomedical engineering, medical devices, biomechanics, biomaterials, bioinstrumentation, clinical engineering, R&D, regulatory documentation, technical review, engineering education, or a similar area.
• Strong English communication skills for understanding instructions and giving precise technical feedback.
• Solid knowledge of core biomedical engineering areas including biomechanics, biomaterials, medical devices, bioinstrumentation, biosignals, imaging systems, physiological systems, tissue engineering, rehabilitation engineering, and biomedical data analysis.
• Ability to judge work against detailed rubrics and identify issues such as incorrect assumptions, faulty calculations, missing units, unsafe guidance, weak clinical or biological reasoning, invented standards, regulatory overstatements, or incomplete explanations.
• Familiarity with tools and workflows such as MATLAB, Python, LabVIEW, SolidWorks, CAD/CAE software, signal processing, medical device documentation, ISO/FDA-related documentation, clinical engineering processes, or biomedical data analysis tools is preferred.
• Experience supporting or leading remote teams of trainers, annotators, reviewers, engineers, technical writers, or QAs is strongly preferred.
• Comfort working in a remote, fast-moving environment with tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Strong organization and attention to detail, with the ability to manage style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and related documentation.
• Experience with AI training, data annotation, LLM evaluation, prompt/response review, technical content QA, biomedical content QA, or rubric-based evaluation is a plus.

Additional information

This is an hourly remote contractor role. The description indicates that there is no immediate project assigned for this position right now, but suitable candidates may be among the first contacted when relevant work becomes available. Access may also extend to future projects through the expert network.

The company also notes that this role contributes to improving biomedical engineering training data for leading AI systems, with a strong emphasis on accuracy, logic, documentation quality, and safety awareness.