Your role

• Work on cutting-edge AI technologies that power future ADAS and automated driving systems

• Apply state-of-the-art machine learning and computer vision techniques to real-world automotive challenges

• Gain hands-on experience with large-scale datasets, modern AI frameworks, and production-oriented development workflows

• Collaborate with experienced researchers and engineers in a highly innovative international environment

• Explore emerging areas such as foundation models, multi-modal learning, behavior prediction, and automated parking

• Develop both research and engineering skills while contributing to products deployed in customer vehicles

Your background

• Master's degree (or close to completion) in Computer Science, Machine Learning, Computer Vision, Robotics, Electrical Engineering, Mathematics, Physics, or a related field

• Strong analytical and problem-solving skills with a solid foundation in mathematics, statistics, and machine learning

• Good understanding of machine learning fundamentals and deep learning concepts

• Academic, internship, research, or project experience in one or more of the following areas:

  • Computer vision (detection, segmentation, tracking, 3D perception)

  • Deep learning techniques (CNNs, Vision Transformers, foundation models)

  • Sequential or temporal modeling and processing

  • Representation learning, self-supervised learning, or generative AI

  • Multi-modal learning

• Hands-on experience with Python and at least one modern ML framework (preferably PyTorch)

• Experience implementing, training, or evaluating machine learning models through coursework, research projects, internships, or personal projects

• Ability to read and understand scientific literature and translate research ideas into practical implementations

• Good communication skills in English

Exceptional recent graduates with strong academic performance, research experience, internships, or outstanding personal projects are encouraged to apply.

Nice to have

• Experience through internships, thesis work, research projects, open-source contributions,  competitions, or personal projects related to AI/ML

• Knowledge of perception, prediction, planning, robotics, or autonomous systems

• Experience with multi-sensor processing (camera, radar, lidar, IMU)

• Familiarity with large language models, vision-language models, or foundation models

• Experience with model optimization, deployment, or efficient inference

• Knowledge of C++ and software engineering best practices

• Exposure to cloud-based or large-scale training environments

• Familiarity with automotive, ADAS, autonomous driving, or robotics applications

• Contributions to scientific publications, patents, open-source projects, or technical competitions

• Experience working with Git, CI/CD, and collaborative development workflows

Why join us?

You can grow at Aptiv. Aptiv provides an inclusive work environment where all individuals can grow and develop, regardless of gender, ethnicity or beliefs.

You can have an impact. Safety is a core Aptiv value; we want a safer world for us and our children, one with: Zero fatalities, Zero injuries, Zero accidents.

You have support. We ensure you have the resources and support you need to take care of your family and your physical and mental health with a competitive health insurance package.

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 work (min. 47 days/yr of remote work, 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

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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.