An early-stage medical device company is developing a wearable biosignal platform with real-time predictive capabilities. The technology targets a significant unmet clinical need, enabling preventative intervention and greater patient independence for those living with treatment-resistant neurological conditions.
This is a founding-team role with meaningful technical ownership and direct influence on product and company direction.
Responsibilities
- Design, develop, and validate machine learning models for real-time biosignal processing and event prediction
- Own the full ML pipeline — from raw signal acquisition and feature engineering through model training, evaluation, and on-device deployment
- Collaborate closely with hardware, firmware, and clinical teams to ensure signal integrity and system performance
- Contribute to regulatory documentation and ensure development practices align with relevant medical device standards
- Drive architectural decisions and help establish engineering best practices as the team scales
Qualifications
- Strong foundation in signal processing, time-series analysis, and applied ML — ideally with physiological or biosignal data (EEG, ECG, EMG, etc.)
- Proficiency in Python and relevant ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Experience with embedded or resource-constrained ML deployment is a strong plus
- Familiarity with medical device development workflows (FDA, IEC 62304, or similar) is a plus
- Excellent problem-solving skills and comfort working in ambiguous, fast-moving environments
- Master’s or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field preferred
