Senior Machine Learning Engineer – Edge AI for Health Wearables
Core
Lead the development of real-time AI models for acoustic biosignal analysis (HR, HRV, Pulse Wave Velocity, Cardiac Output) and deploy them on edge devices for health wearables.
Role type
Senior Machine Learning Engineer (Edge AI / Biosignals)
Builds
Real-time ML models for acoustic biosignal analysis deployed on edge devices
Domain
Health technology / Acoustic biosignals / Embedded systems
Deliverable
production ML models
Required skills
Deep learning (CNN, LSTM, Transformers), Time-series analysis, Model deployment on mobile/embedded systems, Signal processing, Acoustic biosignals knowledge (APG, OAE), TensorFlow Lite, Model quantization, OTA updates, Security and compliance strategies
Preferred skills
Federated learning frameworks (TensorFlow Federated, Flower), Medical-grade device development, Security standards and encryption (AES)
Technologies
TensorFlow, TensorFlow Lite, CNN, LSTM, Transformers
Responsibilities
Design and lead development of advanced ML models for extracting HR, HRV, Pulse Wave Velocity, and Cardiac Output; Ensure robustness of models against noise, motion, and device variability; Drive mobile & edge deployment efforts; Mentor less-experienced engineers and collaborate on firmware, SDK, and backend development; Contribute to security and compliance strategies (GDPR/HIPAA)
Seniority
Senior, hands-on IC
