Generative AI Engineer for Health Multimodal Biosignals

USound GmbH; Österreich; Vor Ort; EUR 43.000 - 55.000; Vollzeit

Benefits dieser Stelle

Lunch subsidies

Language courses

Well-being subsidies

Summer childcare subsidies

Free parking

Zusammenfassung

USound GmbH in Graz, Austria, is seeking an AI Engineer focusing on Generative and Multimodal Health AI to explore cutting-edge methods such as self-supervised learning for biosignal modeling. The role emphasizes edge-friendly architectures and cross-functional collaboration.

You will work with firmware and clinical teams to evaluate models on multimodal time-series data and contribute to a ground-breaking health AI platform. A Master’s or PhD in AI/ML and 4–5 years of experience are expected.

Qualifikationen

• Master’s or PhD in AI, Machine Learning, Computer Science, or Biomedical Engineering with AI focus.
• Experience with generative/self-supervised models and multimodal data is highly desirable.
• 4–5 years of experience in ML/AI, ideally in research-heavy or applied roles.
• Strong background in generative models and self-supervised learning.

Aufgaben

• Develop self-supervised and generative approaches (contrastive learning, VAEs, diffusion models) for acoustic biosignal representation.
• Research multimodal fusion (acoustic biosignals, motion sensors, hearing data) for robust health insights.
• Prototype edge-friendly architectures optimized for low-power real-time inference.
• Collaborate with firmware and clinical teams to validate innovative AI solutions.

Kenntnisse

Generative models

Self-supervised learning

Multimodal data

PyTorch

TensorFlow

ML research

Ausbildung

Master's or PhD in AI/ML/CS/ Biomedical Eng with AI focus

Tools

PyTorch

TensorFlow

Jobbeschreibung

USound GmbH in Graz, Austria, is seeking an AI Engineer focusing on Generative and Multimodal Health AI to explore cutting-edge methods such as self-supervised learning for biosignal modeling. The role emphasizes edge-friendly architectures and cross-functional collaboration.

You will work with firmware and clinical teams to evaluate models on multimodal time-series data and contribute to a ground-breaking health AI platform. A Master’s or PhD in AI/ML and 4–5 years of experience are expected.