ML Engineer - Biosignal AI for Wearables (Flexible Hours)

Almaz Capital; Graz; On-site; EUR 37,000 - 45,000; Full time

Benefits offered by this job

Lunch subsidies

Language courses

Well-being subsidies

Summer childcare subsidies

Free parking and canteen

Job summary

USound seeks a Machine Learning Engineer to advance acoustic biosignal analysis and real-time AI on mobile devices. You will contribute to CNN/LSTM models for biosignals and help deploy lightweight AI on embedded platforms, collaborating with firmware teams.

Ideal candidates have 2–3 years in ML/AI, solid TensorFlow/PyTorch knowledge, and a background in signal processing. This role offers a path to impact wearable health tech with flexible, goal-oriented work environment.

Qualifications

• 2–3 years of ML/AI experience, preferably with time-series or biosignal data.
• Solid understanding of TensorFlow or PyTorch.
• Familiarity with signal processing techniques (e.g., filtering, peak detection).

Responsibilities

• Contribute to deep learning models for acoustic biosignals (e.g., APG).
• Implement algorithms for health indicators from biosignals.
• Assist in making models robust to motion artifacts and noise.
• Optimize ML pipelines for mobile deployment (TensorFlow Lite).
• Collaborate with senior engineers and firmware teams to bring AI into production.

Skills

ML/AI experience

Time-series biosignal data

TensorFlow or PyTorch

Signal processing basics

Education

Bachelor’s or Master’s in CS/EE/Data Science

Tools

TensorFlow Lite

Job description

USound seeks a Machine Learning Engineer to advance acoustic biosignal analysis and real-time AI on mobile devices. You will contribute to CNN/LSTM models for biosignals and help deploy lightweight AI on embedded platforms, collaborating with firmware teams.

Ideal candidates have 2–3 years in ML/AI, solid TensorFlow/PyTorch knowledge, and a background in signal processing. This role offers a path to impact wearable health tech with flexible, goal-oriented work environment.