Senior Radar Machine Learning Engineer (f/m/d)
Aptiv is one of the leading Automotive suppliers and the forefront of solving mobility's toughest challenges. As a large technology company, we are looking for a new talent for one of our leading Tech Centers for Artificial Intelligence in Wuppertal, Germany. We offer the chance to work in a challenging technical environment where science is transferred into real products. There, you can work together with a fantastic, passionate young, international team of technical experts from around the globe to develop new sensors, algorithms and platforms to shape the future of mobility.
Good perception is essential to extract the necessary information about the environment for future autonomous vehicles. We are looking for a passionate AI/ML engineer with a deep understanding for technology. The candidate shall have the capability to transfer the latest AI/ML techniques to combine it with Aptivs latest radar sensor technology to create market leading perception solutions. In order to turn ideas into prototypes, demonstrations and finally into products, the candidate needs to have a strong hands-on spirit. You will be working with exciting new sensor technology of one of the leading automotive radar suppliers.
Master or Ph.D. in science, technology, physics, engineering and mathematics or a related field
At least 3 years of professional experience in a research oriented environment or in industry, preferably in the area of radar technology and / or AI / ML
Excellent analytical skills and a good mathematical background with deep mathematical understanding
Fluent in modern programming languages, such as C/C++, Python, Cuda or R
Experience in one or more of the following fields:
Modern radar signal processing methods
Deep learning and other modern machine learning methods
Good English language skills and preferably proficient German language skills
Experience in developing software as part of a team
Experience with deep learning toolkits like Theano, Pytorch, Tensor Flow, etc.
Experience in the field of real-time and embedded systems
Autonomous driving or ADAS experience
Familiarity with CUDA, Git, CMake, continuous integration tools
Proven track record of publications in relevant conferences (CVPR, NIPS, ICCV, ICRA, Fusion, ...)