Working Student Interior Sensing ML
Core
Developing AI algorithms for in-cabin sensing to detect seat occupancy, left-behind objects, and seat belt usage in vehicles.
Role type
Working Student Machine Learning Engineer
Builds
In-cabin sensing solutions for autonomous driving and driver assistance systems
Domain
Automotive / Machine Learning
Deliverable
production ML models
Required skills
Python programming, machine learning frameworks (TensorFlow, Keras, Caffe, Pytorch, fast.ai), data preparation, data collection, neural network training and evaluation
Preferred skills
German language skills
Technologies
Python, TensorFlow, Keras, Caffe, PyTorch, fast.ai
Responsibilities
Support data preparation and processing, data collection, and training and evaluation of neural networks for advanced engineering applications
Seniority
Student / Working Student
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