Working Student Multi-Fidelity Test Optimization

• You will support the development of intelligent, innovative automated evaluation systems for our in-car LLM-based assistant.
• Furthermore, you contribute to the design and implementation of test optimization approaches across testing environments, ranging from low-fidelity software execution to high-fidelity in-car testing.
• In addition, you help shape our product and process portfolios with your own ideas.
• Moreover, you contribute to close collaboration with suppliers and internal teams, exchanging insights and joining technical discussions driving innovation in automotive AI.

• Studies in computer science, mathematics, physics, or a related discipline.
• Strong programming skills in Python 3, ideally with experience in machine learning frameworks such as TensorFlow or PyTorch.
• Hands-on experience or strong interest in evaluating AI systems, including designing evaluation frameworks and performance measurement.
• Interest in applying optimization approaches to real-life problems.
• Enthusiasm for developing automated, scalable, and reliable applications for in-car systems.
• Motivation to engage in application-oriented research problems.
• Business-fluent English; German language skills are a plus.

Do you enjoy collaborating with an international team and want to help drive innovation in automotive AI? Then Apply now!