Computer Vision & AI Intern- Fall 2025

Job descriptions may display in multiple languages based on your language selection. What we offer: At Magna, you can expect an engaging and dynamic environment where you can help to develop industry-leading automotive technologies. We invest in our employees, providing them with the support and resources they need to succeed. As a member of our global team, you can expect exciting, varied responsibilities as well as a wide range of development prospects. Because we believe that your career path should be as unique as you are. Group Summary: Magna is more than one of the world’s largest suppliers in the automotive space. We are a mobility technology company built to innovate, with a global, entrepreneurial-minded team. With 65 years of expertise, our ecosystem of interconnected products combined with our complete vehicle expertise uniquely positions us to advance mobility in an expanded transportation landscape. Job Responsibilities: Position Overview Magna Corporate R&D Intern program provides students the opportunity to be a key player within the organization. We seek a self-motivated intern to support our research team in projects focused on Computer Vision, Deep Learning, Image segmentation, and Pose estimation to contribute to new technology development in localization and 3D scene understanding/reconstruction. Essential Duties and Responsibilities: Supports the team in the industrialization of the existing 6D pose estimation pipelines. Work with an existing vision, DL model, and toolset and improve aspects of it. Support the research and development of new DL/ML algorithms in object detection, segmentation, and 6D pose estimation domains. Qualifications: Experience building systems based on machine learning and/or deep learning methods. Programming experience with Python/ C /MATLAB, ROS/ROS2 Hands-on experience with deep learning frameworks such TensorFlow, PyTorch, etc. Good hands-on experience with computer vision algorithms and libraries, such as Open CV, Development experience in a Linux environment (Ubuntu is preferred) Self-starter and able to work in a collaborative and result-oriented environment. Education / Experience Current enrollment in computer science, electrical engineering, computer Engineering, Mechanical Engineering, or robotics with emphasis on computer vision and machine learning degree-seeking program at the Graduate-level Special Knowledge / Skills: Experience with DL/ML is required. Hands-on experience with deep learning models for image/video understanding and pose estimation is a plus. Strong knowledge of programming techniques, especially for parallel architectures, is a plus. Physical Demands / Work Environment: Normal amount of sitting or standing, average mobility to move around an office (Troy, MI) environment, able to conduct a normal amount of work at a computer. Awareness, Unity, Empowerment: At Magna, we believe that a diverse workforce is critical to our success. That’s why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law. Mitarbeiterkategorie: Student/in Magna-Gruppe: Magna Corporate Wir haben eine Zukunft vor Augen, in der wir ohne Grenzen leben und uns frei bewegen können. Deshalb entwickeln wir Technologien, Systeme und Konzepte, die Fahrzeuge sicherer und sauberer machen – für unsere Gesellschaft, den Planeten und vor allem uns Menschen. Bei Magna trägst du zur Elektrifizierung der Mobilität bei und arbeitest an der Zukunft der autonomen Fahrassistenz und anderen bahnbrechenden Technologien. Lass uns gemeinsam die Zukunft der Mobilität gestalten. Erfahre mehr über uns: Nachhaltigkeit Innovation Interview-Tipps