Student Interior Sensing ML

Shaping the Future of Mobility

APTIV is one of the largest automotive suppliers and a global technology leader, with more than 180,000 employees worldwide. We tackle mobility's toughest challenges and deliver market-relevant solutions for our customers. One of the key technologies driving the advancement of modern driver assistance systems and autonomous driving is Machine Learning (ML) and Artificial Intelligence (AI).

We are looking for talented students who can contribute fresh ideas and support us in developing the next generation of AI algorithms.

The team you will be working with develops solutions for in-cabin sensing. The goal is to determine, among other things, which seats are occupied, whether objects have been left behind in the vehicle, and whether passengers are wearing their seat belts correctly. In addition, we work on many other exciting topics.

If you are looking for an opportunity to work in industry on practical applications and real-world challenges, we would love to hear from you!

We also offer interesting Master's thesis topics as an attractive opportunity for your next academic and professional step.

• Provide general support in the field of Machine Learning for advanced engineering applications, particularly in data preparation and processing, data collection, as well as the training and evaluation of neural networks.

• You are enrolled at a German university and studying Electrical Engineering, Computer Science, or a related field.
• You have the ability to program independently in Python.
• You have practical experience with at least one machine-learning framework such as Tensor Flow, Keras, Caffe, PyTorch, fast.ai, or similar.
• You have good English skills;
  German language skills are considered an advantage.
• You are looking for a challenging role and enjoy working as part of a team.

• Hourly-paid position.
• Flexible working hours.
• Structured onboarding process.
• Attractive training and development plan.
• Learning, professional growth, and development in a globally recognized international environment.