At APTIV, 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 detection, traffic sign and traffic light recognition, driver drowsiness sensing, seat occupancy monitoring, child presence detection, and hand gesture recognition.
APTIV is a global leader in radar and camera technology and a well-established supplier of sensing and compute hardware as well as software solutions. In this fast growing and innovative technology area, you will be working in an international team of computer vision and machine learning experts to shape the future of mobility with us.
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Your Role:
- Develop Computer Vision algorithms in embedded C++ for automotive embedded platforms
- Optimize algorithms to meet runtime/memory restrictions
- Develop data processing pipelines for Computer Vision development and Machine Learning Training in Python
- Work in an agile and international SW development team
Your Background:
- Master's degree in computer science, electrical engineering or a related field
- Strong software development skills in embedded C++ and Python
- Passion for clean, high-quality, well-tested, and documented code
- Practical experience with classical Computer Vision algorithms and PyTorch or other common Machine Learning frameworks would be an advantage
Your Benefits at Aptiv:
- Private health care (Signal Iduna) and Life insurance for you and your beloved ones
- Well-Being Program that includes regular webinars, workshops, and networking events
- Hybrid and flexible working hours
- Employee Pension Plan paid by the employer (you get + 3,5% on each gross salary)
- Access to sports groups and Multisport card
- Flexible working hours
Apply today, and together let's change tomorrow!
#LI-BR1 #LI-DS2
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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.