• Develop applied Al models for real-time perception, classification, and situational understanding
• Work with multi-modal data
• Build scalable, low-latency inference pipelines for edge and hybrid (onboard + offline) environments
• Design and evaluate Al-based decision support systems (rule+ML or hybrid)
• Collaborate with software, platform, and integration teams to deploy on real hardware
• Maintain focus on robustness, explainability, and safety

• Hold an MSc or PhD in Computer Science or closely related fields in machine learning, signal processing
• Strang background in machine learning (deep learning, statistical learning, representation learning)
• Practical experience in sensor data classification, signal exploitation, or computer vision
• Familiar with Python, Pytorch,
• Strang software engineering standards (Cl/CD, testing, modularity)
• Fluent in English and German

Nice to have

• Experience in building latency-sensitive ML pipelines, model compression or optimization
• Knowledge of decision support systems or reinforcement learning
• Background in Al robustness, interpretability

It is a matter of course for us to offer you optimal working conditions. These include, for example:

• A strong team spirit.
• An exciting, diverse, and innovative work environment and a pleasant working atmosphere with an open corporate culture and flat hierarchies.
• Hybrid working in the Munich office and remotely (e.g. from home).

As well as various benefits: https://www.thyssenkrupp-transrapid.com/de/karriere/arbeiten-bei-uns

thyssenkrupp Transrapid GmbH

TechCenter Control Technology

Kirsten Harling

kirsten.harling@thyssenkrupp.com

Firmen aus der Branche Personalvermittlung bitten wir höflichst, von Anfragen abzusehen.