Machine Learning Engineer – Acoustic Biosignal Analysis
Core
Building deep learning models for real-time acoustic biosignal processing and health insights in wearables.
Role type
Early-career Machine Learning Engineer (acoustic biosignals)
Builds
Real-time mobile AI models for health monitoring
Domain
Wearables / Healthcare / Acoustic Signal Processing
Deliverable
production ML models
Required skills
Deep learning (CNN, LSTM), TensorFlow or PyTorch, Signal processing (filtering, peak detection), Mobile deployment (TensorFlow Lite), Embedded/edge AI
Preferred skills
Biosignal toolkits (NeuroKit2, HeartPy), Wearable device experience, Healthcare application experience
Responsibilities
Contribute to deep learning models for acoustic biosignals, Implement algorithms for HR, HRV, and vascular health indicators, Optimize ML pipelines for mobile deployment, Assist in making models robust to motion artifacts and noise, Collaborate with senior engineers and firmware teams
Seniority
Early-career, hands-on IC