Job descriptions may display in multiple languages based on your language selection.
What we offer:Job Responsibilities:
Position Overview
Magna’s ADAS technologies are shaping an autonomous future and improving lives. The ADAS Intern/Co-op supports the ADAS Environmental Modelling teams by integrating, developing, testing, and debugging low-speed ADAS algorithms such as parking, trailering, surround view, and camera calibration, as well as high-speed sensor fusion algorithms.
Essential Duties and Responsibilities:
- Develop building blocks for ADAS features and algorithms
- Design and implement conventional image processing algorithms
- Design, develop/tune, and optimize deep learning models for ADAS computer vision features
- Demonstrate knowledge of late (object-level) and early (raw-data) sensor fusion
- Create or modify test cases based on requirements to cover new or modified functionality
- Debug and root-cause issues
- Report and document issues; propose corrections
- Perform system testing on bench and in vehicles to ensure the product functions and performs per customer requirements
Qualifications:
- Holds bachelor’s degree in engineering
- Valid Driver’s license
Education / Experience
- Enrolled in a master’s or PhD degree program in Mechanical Engineering / Electrical Engineering / Automotive Engineering/ Computer Science or equivalent
Special Knowledge / Skills:
Mandatory:
- Experience in Digital Image Processing or Machine Learning or vehicle dynamics OR control systems OR digital signal processing through coursework or industry experience
- Coursework or project with vehicle simulation/testing
- Experience with C/C++, Python
- MS Office Tools knowledge
- Basic knowledge of ADAS features
- Working knowledge in structured engineering approach
- troubleshooting and debugging skills
Preferred:
- Experience in ADAS/AD academic/industry projects
- Execution of test suites in a model/software in the loop environment (MIL/SIL)
- Working knowledge in development of portable, reusable and modular software in automotive environment.
Physical Demands / Work Environment:
- Normal amount of sitting or standing, average mobility to move around an office environment, able to conduct normal amount of work at a computer.
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.
AI-Assisted Screening Disclosure
As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.
Under conditions defined by applicable law, you may have the right to request an explanation of how AI is used to support decision-making.
If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.
Worker Type:
Group:
