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Job Responsibilities:
POSITION SUMMARY:
The Machine Learning Engineer will play a pivotal role in driving innovation and operational efficiency through data-driven solutions leveraging machine learning and artificial intelligence. You will be responsible for designing, developing, and deploying machine learning models that enhance product quality, optimize supply chain logistics, improve predictive maintenance, and support intelligent manufacturing processes. Working closely with cross-functional teams including engineering, IT, and operations, you will leverage large-scale data from manufacturing systems, sensors, and enterprise platforms to build scalable ML solutions. Your work will directly contribute to smarter decision-making, reduced downtime and improving quality.
MINIMUM JOB REQUIREMENTS:
SKILLS AND COMPETENCIES:
JOB RESPONSIBILITIES:
Execute ML / AI projects related to but not limited to the following
Advanced Vision Systems
Advanced autonomous part picking
Equipment performance machine learning and predictive maintenance
OEE Improvements
Cycle Time Improvements
Research and benchmark of new / existing smart factory ML solutions measures at other Magna plants or suppliers Identify how technical solutions apply to operational and business needs Understands and uses computer science fundamentals, including data structures, algorithms, computability, complexity, and computer architectures. Uses exceptional mathematical skills, to perform computations and work with the algorithms involved in AI and Machine learning. Build algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production. Analyze large, complex datasets to extract insights and decide on the appropriate technique Develop and manage cloud-based computing and data management. Understand and work within KPIs, metrics, and other monitoring tools to monitor the operational performance of our factories Develop from-end UI’s Report out to the divisional and Magna group level leadership on smart factory solutions initiatives, explaining technical concepts and analysis implications clearly to a wide audience Collaborate closely with IT, operations and engineering to reach operational excellence Manage suppliers and vendors and develop / control project deliverables. Deal with vendors – Excellent verbal and written communication skills are required. Collaborate other Machine learning Engineers within Magna as well as with your Regional Smart Factory Solutions lead Support colleagues in sourcing equipment and technology that improves the division’s smart factory solutions performance
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.
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