Intern - Engineering ADAS Perception Features
At a glance
Junior Machine Learning Engineering role at Magna. Auburn Hills · part-time.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build components for low- and high-speed ADAS features, including parking, trailering and sensor fusion
- Create and tune image-processing and deep-learning methods for ADAS computer vision
- Write or revise tests against requirements, then investigate faults and document proposed fixes
- Test system behavior on benches and in vehicles against customer requirements
What you bring
- You hold an engineering bachelor's degree and are enrolled in a master's or PhD program in a related field
- Coursework or industry work in image processing, machine learning, vehicle dynamics, control systems or signal processing
- You have completed coursework or a project involving vehicle simulation or testing
- You can work with C/C++ and Python, and bring troubleshooting and debugging skills
Who this fits
This student co-op suits someone pursuing graduate study who wants hands-on ADAS algorithm, testing and debugging work. The role includes testing both on a bench and in vehicles, and requires a valid driver's license.
From the employer
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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:
Transforming mobility. Making automotive technology that is smarter, cleaner, safer and lighter. That’s what we’re passionate about at Magna Electronics, and we do it by creating world-class Electronic systems. We are a premier supplier for the global automotive industry with full capabilities in design, development, testing and manufacturing of complex Electronic systems. Our name stands for quality, environmental consciousness, and safety. Innovation is what drives us and we drive innovation. Dream big and create the future of mobility at Magna Electronics.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.
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.
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:
Student / Co-OpGroup:
Magna Electronics