AI/ML Machine learning engineer ADAS algorithms
As a fast-growing technology company Aptiv is always interested in hiring new talents. We are looking for talented Machine Learning Experts who are familiar with state of the art machine learning techniques like deep neural networks from academia or industry. With a good mathematical and scientific background, this specialist shall create new solutions for prediction & planning, fusion and control problems which perform beyond the current state of the art.
You will work together with experts from around the globe with various professions to finally bring these new systems to the newest automotive platforms.
Required
• Master or Ph.D. in computer science, machine learning or related field
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• Excellent analytical skills and a good mathematical background
• Educational background including machine learning and data science
• Software engineering experience, ability to work from scratch as well as on existing big code basis
• Professional experience in at least one of following fields:
o Deep neural networks and other state of the art ML techniques for detection, segmentation fusion and other applications
o Active, reinforcement learning, imitation learning
o Time series prediction with modern ML techniques
o NLP, genAI, chat AI models
o Model, rule and learning based decision making
o ML techniques CNN, RNN, transformers, graph CNN
• Systematic, goal and outcome oriented working style
• Professional experience (2 years +) in AI development frameworks Tensorflow and/or Pytorch
• Professional Skills in Python, (C++)
Bonus
• Understanding of edge processing / Embedded AI and related methods like RUST is a plus
• Proven track record of publications in relevant conferences (CVPR, NIPS, ICCV, ICRA, Fusion, and others...) and scientific background on relevant topics
• Understanding of autonomy levels and features in ADAS and parking applications
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Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law.