Biomedical Engineering Quality Assurance Lead

Role overview

This remote contractor position is for a Biomedical Engineering Quality Assurance Lead who will help maintain high standards across biomedical engineering AI training initiatives. The work focuses on checking the quality and consistency of both AI-generated biomedical content and the output of trainers and QA reviewers, then giving clear written feedback to improve accuracy and reliability.

You will assess whether content follows the project rubric and rules, with attention to technical correctness, biomedical reasoning, calculation accuracy, standards awareness, regulatory awareness, unit consistency, safety, clarity, formatting, and instruction adherence. The role also includes identifying repeated quality problems, sharing updates with trainers and QAs, assisting with onboarding, maintaining documentation, and re-engaging contributors who are not actively working.

This opportunity is with a fast-growing AI data services company that provides training data for leading AI companies and foundation model labs. Your contribution will support the development of high-quality AI systems by ensuring biomedical engineering training data is well-explained, logically sound, documented properly, safety-conscious, and aligned with client expectations.

There is no active project attached to this role at the moment. If you are a fit, you may be contacted first when relevant work becomes available and may also gain access to future projects through the expert network.

Responsibilities

• Review biomedical engineering items for quality issues and share ongoing feedback through direct messages, escalating serious or repeated concerns when needed.
• Check AI-generated explanations, calculations, device reasoning, biomaterials content, biosignal and bioinstrumentation workflows, diagrams, and solution steps for technical accuracy and clarity.
• Keep trainers and QAs informed on Discord about guideline changes, workflow updates, project expectations, and biomedical-specific review standards.
• Answer questions from trainers and QAs promptly and clearly, especially on assumptions, units, formulas, safety, regulatory considerations, and rubric interpretation.
• Reach out to inactive contributors, encourage them to resume work, track follow-ups, and flag availability problems when necessary.
• Build and maintain project documentation such as style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Organize and lead onboarding or training calls to explain expectations, workflows, rubrics, and quality requirements.
• Make sure trainers and QAs apply the biomedical engineering guidelines consistently as project needs change.
• Identify unsafe, misleading, or overly confident recommendations, particularly where patient safety, medical devices, diagnostics, imaging, rehabilitation, clinical workflows, or regulatory claims are involved.
• Suggest process improvements and help create scalable QA systems for biomedical engineering AI training projects.

Requirements

• A bachelor’s or master’s degree in Biomedical Engineering, Bioengineering, Medical Engineering, Biomechanical Engineering, or a closely related discipline; equivalent engineering backgrounds with a biomedical focus may also be suitable.
• Strong command of English for following instructions, collaborating with teams, and delivering clear technical feedback.
• At least 3 years of professional experience in biomedical engineering or related areas such as medical devices, biomechanics, biomaterials, bioinstrumentation, clinical engineering, R&D, regulatory documentation, technical review, or engineering education.
• Good working knowledge of core biomedical engineering areas, including biomechanics, biomaterials, medical devices, biosignals, imaging systems, physiological systems, tissue engineering, rehabilitation engineering, and biomedical data analysis.
• Ability to review work against detailed rubrics and catch problems such as incorrect assumptions, calculation errors, missing units, unsafe guidance, weak biological or clinical logic, unsupported standards references, overblown regulatory claims, or incomplete explanations.
• Preferred familiarity with tools and workflows like MATLAB, Python, LabVIEW, SolidWorks, CAD/CAE software, signal processing, device documentation, ISO/FDA-related documentation, clinical engineering, or biomedical data analysis tools.
• Prior experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, or QAs is strongly preferred.
• Comfort using remote collaboration and project tools such as Discord, Google Sheets, Google Docs, dashboards, trackers, and project management platforms.
• Very strong attention to detail and organization, with the ability to manage style guides, FAQs, trackers, onboarding content, calibration tasks, and related documentation.
• Experience with AI training, annotation, large language model evaluation, technical content QA, biomedical content QA, or rubric-based review is a strong advantage.

Additional information

This is an hourly remote contractor role. The position is described as contract-based and remote, with no immediate project currently assigned. Qualified candidates may be approached later for suitable opportunities and future projects within the expert network.

Work focus

The main focus is biomedical engineering quality leadership across AI training workflows, including evaluation of technical outputs, reviewer guidance, documentation upkeep, and consistency management for remote teams.