Thesis Machine Learning for Automated Driving (f/m/x)
At a glance
Mid-level Machine Learning Engineering role at BMW Group. Munich.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Compare CLIP, VideoCLIP and BLIP approaches for detecting driving scenarios and concepts
- Frame detection as a temporal, multi-label task using image, object and location inputs
- Help set labeling rules for an expanding set of scenario concepts
- Design compact sensor-fusion models and apply distillation, quantization or pruning
- Build training and evaluation workflows, choose metrics, and check onboard runtime and memory needs
What you bring
- You are studying computer science, electrical engineering, robotics, data science or a related subject
- You have a solid grounding in machine learning and deep learning, ideally with computer vision or multimodal learning experience
- You can work proficiently in Python and have used PyTorch, TensorFlow or another common ML framework
- You bring strong knowledge of model compression methods; transformer sequence-model experience is a plus
Who this fits
This six-month, full-time thesis suits a student interested in automated driving, sensor fusion and embedded or edge ML. The role is based in Munich and starts no earlier than October 1, 2026. You’ll need very good English; German is an advantage.
From the employer
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.