Machine Learning Engineer - Acoustic Biosignal Analysis

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

Machine Learning Engineer – Acoustic Biosignal Analysis

Graz, Austria

USound is disrupting the audio industry, setting new standards in audio experience, and maximizing the degrees of freedom in manufacturing wearables and hearables.

We are leaders in acoustic solutions based on MEMS speakers. Since 2018, we have been enabling our customers to bring new revolutionary audio products to the market. USound achieves this through radical miniaturization, power reduction, and increased production efficiency.

At USound, we’re pioneering the future of in-ear wearables — devices that go beyond music playback to unlock real-time health insights. We’re looking for an early-career Machine Learning Engineer eager to work on AI models for acoustic biosignal processing and real-time mobile deployment.

Responsibilities

• Contribute to deep learning models (CNN, LSTM) for acoustic biosignals (e.g., APG).
• Implement algorithms for HR, HRV, and vascular health indicators.
• 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.

Experience and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical/Biomedical Engineering, or Data Science
• Coursework or projects in Machine Learning, Signal Processing, or Biosignal Analysis are a plus
• 2–3 years of experience in ML/AI, ideally with time-series or biosignal data
• Solid understanding of TensorFlow or PyTorch
• Familiarity with signal processing techniques (e.g., filtering, peak detection)
• Basic experience in deploying AI models on embedded or edge devices
• Strong collaborative mindset and eagerness to learn and grow

Nice-to-have

• Familiarity with biosignal toolkits (NeuroKit2, HeartPy).
• Experience with wearable devices or healthcare applications.

What we offer

• The opportunity to grow along with an internationally active, innovative company and a ground-breaking technology.
• Flexible working time and goal-oriented work environment.
• Collegial environment in a dynamic and dedicated team.
• Range of the annual gross salary from € 45,000 depending on experience, qualifications, etc; legal minimum annual gross salary on a full-time basis: € 37,361.66.
• Additional incentives including bonuses and profit-sharing opportunities.

Benefits: We offer a range of perks including lunch subsidies, language courses, well-being and summer childcare subsidies, future provision, and many more. At our location you will find free parking slots, a canteen and a snack buffet.