Working student Computer Vision / Machine Learning / Artificial Intelligence (m/f/d)

Key Skills

Java Programming, Python Programming, C++, SQL, Aartificial intelligence, Machine learning techniques, Data Visualization, Keras software library, PyTorch, TensorFlow, Fast.ai, Algorithms, Caffe, Neural Networks, Dash framework

Job Description

APTIV is one of the largest automotive suppliers and a global technology leader, with more than 190,000 people worldwide. We address mobility’s toughest challenges and deliver market-relevant solutions for our customers. One key technology for further pushing the boundaries of advanced driver assistance systems and autonomous driving is machine learning/artificial intelligence (AI). We are searching for talented students who bring in new ideas and help to develop our next generation of AI algorithms.

We design, develop, and validate systems to improve safety and comfort in vehicles. This includes the development of innovative computer vision features and machine learning algorithms for interior and exterior cameras. Examples of features are vehicle and pedestrian detection, lane and traffic sign recognition, seat occupancy monitoring, child presence detection, and hand gesture recognition. Further, we develop algorithms which, based on camera, lidar and radar sensor data, can understand complex driving scenarios (e.g. crowded multi-lane highways, inner cities), anticipate the behavior of other road users (e.g. a pedestrian crossing the road or a vehicle changing the lane) and finally make safe and comfortable driving decisions.

If you are looking for an interesting topic for your master’s thesis and want it to be close to the industry and real-world applications, please get in touch! After at least six successful months as a working student, we can offer an interesting topic for your master’s thesis and possibly even a three-year PhD position afterwards.

Your tasks

• In general: Support us in topics related to computer vision and machine learning/artificial intelligence, i.e. algorithm development, data preparation and processing in Python, neural network training, deployment of neural networks for real-time execution, visualization of results, generation of performance statistics etc.
• Example topic 1: Support in building up a training toolchain for lane and road edge detection, creating training and validation data sets, re-training state-of-the-art models on data from our sensors and assessing their performance and runtime.
• Example topic 2: Support the pre-processing of sensor data in order to modify an existing approach for dynamic occupancy grid-based traffic scene prediction using precise maps and localization to work with a perception only system (no maps but camera and radar).
• Example topic 3: Detect if the camera’s view on the street ahead is blocked.

Your profile

• You are enrolled at a German University and are studying Electrical Engineering, Computer Science or similar
• You have practical experience with Computer Vision or Machine Learning algorithms
• You have practical experience with at least one ML framework like Tensorflow, Keras, Caffe, PyTorch, fast.ai etc.
• You are able to program self-reliant in Rust, C++ and/or Python.
• You have good English skills, German skills would be a plus.
• You are looking for a challenging task and like to be part of a team.
• You are living close to Wuppertal or willing to commute.

Interested?

Great! Please apply and make sure to include:

• Cover Letter
• Curriculum Vitae
• Course and grade overview of Bachelor’s and Master’s studies
• Earliest start date and planned duration of your engagement (at least six months