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

BMW Group1 month agoUpdated 16 days agoWorking Student
HybridEnglish requiredGerman is a plus (not required)TechAI, ML & Data Science

At a glance

  • Pay

    Not stated

    Median for Tech in Munich: €17.26/hr, from 100 working-student postings with stated pay in the last 12 months. Salary guide

  • Requirements

    Studies: Computer science, electrical engineering, mechatronics, data science or related

    Languages: English (fluent)

  • Hours & duration

    6 months

  • Good to know

    Thesis possible

  • Benefits

    Flexible hours
  • Employer

    BMW Group · Automotive · 10,000+ employees worldwide · HQ in Munich

    We list 402 open student roles at BMW Group, 330 in Munich. 1,214 more have closed since March 2026. See all BMW Group roles

  • Similar roles

    461 open Tech roles in Munich

    Of these: 33% with no German needed, 56% hybrid or remote, 9% with pay stated.

    59 of the 461 need no German and are hybrid or remote, this role included.

  • Skills in the ad

    Edge MLEmbedded MLPruningComputer visionKnowledge distillationMulti-modal learningTransformersPythonQuantizationCLIPSensor fusionPyTorchBLIPVideoCLIPTensorFlow

Job description

Description provided by BMW Group

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? 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.

Rules that apply:20-hour rule140/280-day ruleWerkstudentenprivilegNet pay calculator

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