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

Bayerische Motoren Werke Aktiengesellschaft; München; Vor Ort; EUR 20.000 - 27.000; Vollzeit

Benefits dieser Stelle

Mentoring

Flexible hours

Mobile work

Housing for students (Munich)

Zusammenfassung

The BMW Group in Munich is offering a 6‑month full‑time thesis position in Machine Learning for Automated Driving. You will work on scalable data collection and multi-modal trigger models that detect driving situations, and help develop and optimize these models end‑to‑end.

Responsibilities include reviewing multi-modal approaches (CLIP/VideoCLIP/BLIP), formalizing tasks for multi-label temporal classification, and shaping a compact fusion architecture with sensor data.

Qualifikationen

• Studies in computer science, electrical engineering, robotics, data science, or related field.
• Strong foundation in machine learning and deep learning.
• Proficient in Python and ML frameworks such as PyTorch or TensorFlow.

Aufgaben

• Review multi-modal approaches for scenario detection, including CLIP, VideoCLIP, and BLIP.
• Formalize tasks as multi-label, multi-modal, temporal classification using image/object/location data.
• Define labeling requirements for scenario concepts.
• Design a compact, multi-modal fusion architecture for processing sensor streams.
• Apply model optimization techniques such as distillation, quantization, and pruning.
• Contribute to training/evaluation pipelines and define evaluation metrics.
• Assess onboard feasibility regarding runtime and memory footprint.

Kenntnisse

Python

PyTorch

TensorFlow

ML

English

Ausbildung

Bachelor/Master student

Tools

PyTorch

TensorFlow

Jobbeschreibung

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

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

Posting Start Date: 9/1/26

Job Location (Long):
Munich, Bayern 80809
Germany

Job Description

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?

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 .