Product Owner – Computer Vision SLAM/ Machine Learning Full-time

High-level Team context:
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 and traffic sign recognition, driver drowsiness sensing, seat occupancy monitoring, child presence detection, and hand gesture recognition.
APTIV is a global leader in 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 would be working in an international team of computer vision and machine learning experts to shape the future of mobility with us.
Computer Vision SLAM / Machine Learning Product Owner
Role:
• Lead and oversee the development of SLAM (Simultaneous Localization and Mapping) algorithms in a cloud-based environment as well as on the edge.
• Integrate machine learning methods to improve SLAM system performance.
• Manage and guide a team of engineers and developers specializing in SLAM and pose graph optimization.
• Conduct research on the latest technologies in computer vision, SLAM, and machine learning.
• Ensure the architectural integrity and scalability of SLAM solutions in cloud platforms.
• Participate in code reviews and adhere to software development best practices.
• Defining and continuously improving machine learning workflows based on best practices in the industry and establishing them within the team
• Filing patent applications to strengthen the APTIV IP footprint
• Working in an Agile SW development team
Required Qualifications:
• Master’s degree + 3 years of relevant experience or PhD degree in computer science, electrical engineering or related field.
• Experience in leading a team technically.
• Expert knowledge in SLAM algorithm or Structure from Motion.
• Profound understanding of pose graph optimization techniques.
• Profound understanding of non-linear optimization techniques such as Levenberg-Marquardt
• Strong software development skills in both C++ and Python and optionally Rust.
• Proven experience in computer vision, particularly in SLAM or Structure from Motion
• Experience with sensor fusion and real-time systems.
• Publications in relevant conferences or journals.
• Experience with GPU programming and optimization.
• Deep understanding of artificial intelligence, model building and evaluation
• Expert knowledge in at least one common ML framework (PyTorch,…)
• Knowledge in Non-Linear Optimization libraries e.g. Ceres
• Knowledge in classical computer vision and camera calibration
• Practical experience with Linux, version control systems (Git), build systems (CMake, Bazel) and code review tools (Gerrit, Gitlab, Bitbucket)
• Fluent in English. Excellent written and verbal communication skills & good interpersonal skills

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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.