AI Engineer: Generative & Multimodal Health AI (Edge)

Almaz Capital; Graz; On-site; EUR 43,000 - 55,000; Full time

Benefits offered by this job

Lunch subsidies

Language courses

Well-being subsidies

Summer childcare subsidies

Future provision

Free parking

Canteen

Snack buffet

Job summary

USound Graz, Austria, is seeking an AI Engineer to advance generative and self-supervised models for acoustic biosignals. You will explore multimodal fusion with motion data and wearables, designing edge-friendly architectures for real-time inference.

Collaborate with firmware and clinical teams; bring innovative AI solutions to health insights from acoustic biosignals. Experience in time-series multimodal data and prototyping is valued.

Qualifications

• Master’s or PhD in AI, ML, CS, 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 in research-heavy or applied roles.

Responsibilities

• Develop self-supervised and generative approaches for acoustic biosignal representation.
• Research multimodal fusion for robust health insights.
• Prototype edge-friendly architectures for low-power real-time inference.
• Collaborate with firmware and clinical teams to validate AI solutions.

Skills

Generative AI

Self-supervised learning

Multimodal data

ML model development

Time-series data

Prototyping

Education

Master’s or PhD in AI/ML/CS or Biomedical Engineering with AI focus

Tools

PyTorch

TensorFlow

Job description

USound Graz, Austria, is seeking an AI Engineer to advance generative and self-supervised models for acoustic biosignals. You will explore multimodal fusion with motion data and wearables, designing edge-friendly architectures for real-time inference.

Collaborate with firmware and clinical teams; bring innovative AI solutions to health insights from acoustic biosignals. Experience in time-series multimodal data and prototyping is valued.