Working Student Multi-Fidelity Test Optimization

WE CANNOT PREDICT THE FUTURE. BUT WE CAN SHAPE IT. SHARE YOUR PASSION. World-leading technologies don’t make it into a BMW until they’ve undergone one of the most challenging journeys imaginable. It takes dynamic teams with outstanding technical skills to take them from the drawing board to the road. That’s why our experts will treat you as part of the team from day one, encourage you to bring your own ideas to the table – and give you the opportunity to really show what you can do. Our team at the BMW Group turns science fiction into reality by applying the latest advances in generative AI, machine learning, computer vision, and natural language processing to industrial use cases. We support the development of our in-car LLM-based assistant and continuously advance test optimization approaches across multiple fidelity levels. Together with experienced AI developers, we explore innovative solutions at the crossroads of AI, linguistics, and computer science.

• 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.