Stage - Data Engineer - ML (H/F)
Core
Design, develop, and validate algorithms to extract reliable physiological and medical information from physical signals collected by connected health devices.
Role type
Intern, Machine Learning Engineer (Signal Processing & Embedded)
Builds
Embedded algorithms for health monitoring devices (e.g., SPO2, heart rate, arrhythmia detection)
Domain
Health tech / Medical devices / Signal Processing
Deliverable
production ML models
Required skills
Signal processing, Machine Learning, Deep Learning, Python, Data analysis
Preferred skills
C programming, PyTorch, TensorFlow
Technologies
Python, PyTorch, TensorFlow, C
Responsibilities
Explore and analyze real physiological datasets to identify relevant markers; Design and develop algorithms combining signal processing, heuristics, and ML/DL; Optimize algorithms for embedded implementation on resource-constrained systems; Define success criteria and evaluate algorithm performance.
