Biomedical Engineering Quality Assurance Lead

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help people start and grow careers teaching AI by consolidating specialized projects, building a unified profile, and making it easy to apply and track work.

OpenTrain AI is hiring directly for this role. As the hiring organization we manage project scope, quality expectations, and contributor onboarding for our biomedical engineering annotation and evaluation work.

About AI Training Work

AI training (data labeling, annotation, and human feedback) is the human side of building modern AI systems. Contributors review, correct, and rate model outputs so models learn accurate, safe, and useful behavior.

This work is remote, flexible, and accessible: many roles need strong domain knowledge or attention to detail rather than prior AI experience, and contributors directly shape how state-of-the-art systems behave.

The Role

We are looking for a Biomedical Engineering Quality Assurance Lead to review AI-generated biomedical engineering content and trainer QA work for accuracy, clarity, and rubric adherence.

This is a part-time contractor role (20+ hours/week), US-only, paying $105/hour. You will deliver precise written feedback, maintain quality documentation, support trainer onboarding and calibration, and escalate safety or regulatory concerns.

• Title: Biomedical Engineering Quality Assurance Lead
• Schedule: 20+ hours per week (part-time contractor)
• Location: United States only (remote)
• Rate: $105 USD per hour

What You'll Do

You will evaluate AI outputs, trainer submissions, and QA work against detailed rubrics, then document and communicate findings so contributors improve and projects remain safe and accurate.

• Review AI-generated explanations, diagrams, problem-solving steps, and trainer QA submissions for correctness and clarity.
• Evaluate calculations, unit consistency, biomedical reasoning, safety considerations, and references to standards or regulatory context.
• Provide precise written feedback and corrective examples to trainers and QAs.
• Produce and maintain documentation: style guidance, FAQs, calibration tasks, honeypots, examples, and onboarding materials.
• Flag recurring quality issues, suggest workflow improvements, and support activation or retraining of inconsistent contributors.
• Escalate instances where AI recommendations could be unsafe, misleading, or overconfident.

Requirements

Candidates must meet the core technical and communication requirements below; we will verify domain expertise and prior professional experience during hiring.

• Bachelor’s or master’s degree in Biomedical Engineering, Bioengineering, Medical Engineering, Biomechanical Engineering, or a closely related field.
• 3+ years of professional experience in biomedical engineering, medical devices, biomechanics, biomaterials, bioinstrumentation, clinical engineering, R&D, regulatory documentation, technical review, or engineering education.
• Strong English communication skills for clear, structured technical feedback and team coordination.
• Ability to evaluate biomedical content against detailed rubrics and identify flaws in assumptions, calculations, units, standards references, or safety reasoning.
• Familiarity with tools or workflows such as MATLAB, Python, LabVIEW, SolidWorks/CAD/CAE, signal processing, medical device documentation, ISO/FDA-related documentation, or biomedical data analysis tools.
• Experience supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, or QAs is strongly preferred.

Helpful Background

The following skills are not required but will help you ramp faster and contribute more impactfully to projects.

• Experience with AI training, data annotation, large language models, prompt or response evaluation, or rubric-based LLM evaluation.
• Comfort working in fast-moving remote environments and collaboration tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Prior involvement with technical QA, calibration exercises, or creating honeypots and calibration tasks for contributor networks.

How It Works

You will contract with OpenTrain AI as a part-time remote contributor. Assignments include reviewing batches of AI outputs and trainer/QAs, writing feedback, and updating project documentation and calibration materials.

Onboarding will include rubric orientation, calibration tasks, and example-driven guidance. Work is paid hourly at the stated rate; scheduling is flexible but consistent weekly hours are expected to meet project needs.

To apply, create or use your OpenTrain account and submit your profile and experience information. We will review applications and share onboarding instructions and calibration tasks for qualified candidates.