Senior Edge AI Engineer for Real-Time Health Wearables

USound GmbH; Österreich; Sur place; EUR 41 000 - 50 000; Plein temps

Avantages offerts par ce poste

Lunch subsidies

Language courses

Well-being subsidies

Summer childcare subsidies

Free parking

Canteen

Snack buffet

Résumé du poste

USound GmbH in Graz, Austria seeks a Senior Machine Learning Engineer to lead real-time AI on edge devices for acoustic biosignals and health wearables.

You will design ML models (CNN, LSTM, Transformers) for HR/HRV/PulseWave Velocity, ensure robustness against noise and motion, and drive mobile/edge deployment using TensorFlow Lite and OTA updates. Collaboration with firmware and backend teams is essential.

Qualifications

• Master’s or PhD in Computer Science, AI, Electrical/Biomedical Engineering, or Embedded Systems.
• Strong background in deep learning, time-series analysis, and model deployment.
• 6+ years in ML/AI with strong focus on time-series / biosignals.
• Proven expertise in deep learning and signal processing.
• Hands-on experience deploying ML models on mobile or embedded systems.
• Strong knowledge of acoustic biosignals (APG, OAE).
• Comfortable working in a small, cross-functional environment.

Responsabilités

• Design and lead development of advanced ML models (CNN, LSTM, Transformers) for extracting HR, HRV, PulseWave Velocity, and Cardiac Output.
• Ensure robustness of models against noise, motion, and device variability.
• Drive mobile & edge deployment efforts (TensorFlow Lite, quantization, OTA updates).
• Mentor less-experienced engineers and work closely with firmware, SDK, and backend development.
• Contribute to security and compliance strategies (GDPR/HIPAA).

Formation

Master’s degree in Computer Science/AI/ Electrical/Biomedical Engineering/Embedded Systems

PhD in related field

Outils

TensorFlow Lite

Edge deployment

Description du poste

USound GmbH in Graz, Austria seeks a Senior Machine Learning Engineer to lead real-time AI on edge devices for acoustic biosignals and health wearables.

You will design ML models (CNN, LSTM, Transformers) for HR/HRV/PulseWave Velocity, ensure robustness against noise and motion, and drive mobile/edge deployment using TensorFlow Lite and OTA updates. Collaboration with firmware and backend teams is essential.