About this role
If you are a biomedical engineer who thrives on technical precision, applied problem-solving, and rigorous engineering reasoning in health and life-science contexts, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex biomedical engineering concepts. We are looking for biomedical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Biomedical Engineer will directly help improve the world’s premier AI models—and play an important role in shaping the future of AI. 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.
Requirements
- 4+ years of professional biomedical engineering experience, with significant hands-on work in one or more areas such as medical devices, biomechanics, biomaterials, tissue engineering, bioinstrumentation, imaging systems, signals & systems (physiologic), rehabilitation engineering, clinical engineering, quality/regulatory, manufacturing/validation, or a closely related specialty.
- Deep knowledge of biomedical engineering fundamentals, such as physiology for engineers, transport phenomena in biological systems, biomechanics, materials behavior in biological environments, biosignals, sensor/measurement systems, and systems modeling (depending on specialty).
- Strong comfort with technical assumptions, constraints, unit consistency, and defensible reasoning (including limitations, uncertainty, and safety considerations).
- Bachelor’s degree in Biomedical Engineering (or closely related) required; Master’s/PhD or advanced credentials strongly preferred.
- Experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus.
- Familiarity with any of the following is a plus (not required): ISO 13485, IEC 60601, ISO 14971, FDA design controls (21 CFR 820), verification & validation, risk management, biocompatibility concepts (ISO 10993), or clinical workflow constraints.
Responsibilities
- Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across biomedical engineering topics.
- Challenge advanced language models with realistic biomedical engineering scenarios, calculations, and design/analysis reasoning tasks.
- Review and refine AI-generated prompts, model responses, explanations, and step-by-step solutions (including unit handling and correct interpretation of constraints).
- Provide structured feedback that identifies factual errors, unsafe recommendations, unsupported clinical claims, missing assumptions, invalid simplifications, misuse of standards, or incomplete reasoning.
- Assess model performance on topics such as: Biomechanics, Bioinstrumentation & sensors, Biomedical signals, Medical device design, Biomaterials, Imaging & measurement, Verification/validation & risk
- Help shape AI communication standards for biomedical content, including how models explain assumptions, risk/limitations, what must be verified experimentally, and when to escalate to clinical/regulatory experts.
- Ensure AI-generated content reflects responsible biomedical engineering practice—especially around patient safety, clinical claims, and regulatory-sensitive topics.
Additional skills
- Medical Device Design
- Biomechanics
- Biomaterials
- Tissue Engineering
- Bioinstrumentation
- Physiological Signal Processing
- Signals & Systems
- Medical Imaging Systems
- Rehabilitation Engineering
- Clinical Engineering
- Physiology
- Transport Phenomena
- Systems Modeling
- Sensor Design
- Data Acquisition (DAQ)
- MATLAB
- Python
- LabVIEW
- SolidWorks
- Finite Element Analysis (FEA)
- Design of Experiments (DoE)
- Verification & Validation (V&V)
- Risk Management (ISO 14971)
- ISO 13485
- IEC 60601
- FDA Design Controls (21 CFR 820)
- Biocompatibility (ISO 10993)
- Quality Management Systems (QMS)
- Manufacturing Validation
- AI Data Annotation
