Munich Thesis End To End Autonomous Driving (Fmx) By 80809

Job description

Our End-to-End Autonomous Driving and Predevelopment team at BMW Group drives forward state-of-the-art neural network architectures for autonomous driving, including multi-modal perception backbones, foundation models, and sparse representations. As an intern, you support us in developing novel strategies for selecting representative datasets and in testing diverse training approaches to use these datasets effectively.

What awaits you? You collaborate closely with the BMW End-to-End Autonomous Driving and Predevelopment team. Furthermore, you support the exploration of state-of-the-art techniques and architectures in end-to-end autonomous driving, vision-language models, and embodied AI. In addition, you get the opportunity to experience your research findings in real vehicle demos. Moreover, you have access to a large compute cluster to carry out your research.

Furthermore, you have the opportunity to publish your results together with your supervisors. Please note that your thesis must be supervised by a university throughout the project. What should you bring along? Studies in computer science, robotics, or a related field with a focus on machine learning. Excellent knowledge of machine learning and computer vision. Strong programming skills. Proficiency in Python and deep learning frameworks such as PyTorch.

Good English skills. Are you enthusiastic about new technologies and eager to shape the future of autonomous driving? Then Apply now! What do we offer? Comprehensive mentoring & onboarding. Personal & professional development. Flexible working hours. Mobile work. Attractive & fair compensation. Apartments for students (subject to availability & only at the Munich location). And much more, see bmw.jobs/waswirbieten Start date: earliest start 12/01/2026 Duration: 6 months Working hours: Full-time You can find helpful tips on your application and the application process here.

At the BMW Group, we place great value on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants. More about this here.