Advanced Driver Assistance Systems Munich 01.09.2026

Thesis Machine Learning for Automated Driving (f/m/x)

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 develops new approaches for scalable data collection in automated driving. We focus on compact, multi-modal trigger models that reliably and precisely detect relevant driving situations. As part of your thesis, you support our team in developing and optimizing these models.

What awaits you?

  • You will support the review and assessment of multi-modal approaches for scenario and concept detection, including CLIP, VideoCLIP, and BLIP.
  • Furthermore, you help formalize the task as a multi-label, multi-modal, temporal classification problem using image, object, and location data.
  • In addition, you support the definition of labeling requirements for a growing set of scenario concepts.
  • Moreover, you assist in designing a compact, multi-modal fusion architecture for processing multiple sensor data streams.
  • Furthermore, you help apply model optimization techniques such as knowledge distillation, quantization, and pruning.
  • In addition, you contribute to building the training and evaluation pipeline and defining suitable evaluation metrics.
  • Moreover, you support the assessment of onboard feasibility regarding runtime and memory footprint.

 

What should you bring along?

  • Studies in computer science, electrical engineering, robotics, data science, or a related field
  • Strong foundation in machine learning and deep learning, ideally with experience in computer vision or multi-modal learning
  • Proficient in Python and experienced with common ML frameworks such as PyTorch or TensorFlow
  • In-depth knowledge of model optimization techniques such as quantization, pruning, or distillation as well as experience with sequence models such as transformers is a plus
  • Interest in automated driving, sensor fusion, and embedded or edge ML deployment
  • Structured and precise working approach along with strong team spirit
  • Very good English skills; German skills are a plus

 

Would you like to help shape compact, multi-modal AI models for automated 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 date 10/01/2026

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 importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants. Learn more here.

Thesis Machine Learning for Automated Driving (f/m/x)

com.bmw.grpw.core.models.jobfinder.IdDisplayItem@7e240fd0
20260901
Automotive
Munich
Germany
Legal Entity:
BMW AG
BMW Group
Location:
Munich
Job Field:
Advanced Driver Assistance Systems
Job Id:
182986
Publication Date:
01.09.2026
Internship
Full-time