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What we offer:Job Responsibilities:
• Design and implement ML based tools for:
• Scenario classification, tagging, and search
• Anomaly detection in test data
• Sensor data quality assessment (vision, radar, LiDAR)
• Behavior analytics, KPI extraction, and automated reporting
• Build smart assistants to support test prioritization, risk based testing, and regression selection.
• Create scalable pipelines to ingest, preprocess, and transform camera, radar, and LiDAR datasets.
• Develop automated data curation workflows (filtering, clustering, stratified sampling).
• Implement model agnostic interfaces for dataset replay in SIL/HIL environments.
• Develop applications for:
• Ground truth generation (manual & semi automated)
• Sensor fusion visualization and annotation tooling
• Offline inference benchmarking and KPI trend analysis
• Integrate applications into existing verification ecosystems (HIL benches, simulation platforms, CI/CD).
• Build ML modules that plug into:
• SIL/HIL simulation frameworks
• Scenario orchestration and execution engines
• Continuous integration & validation pipelines
• Work closely with system verification teams to define KPIs, metrics, and evaluation frameworks.
• Create reproducible ML workflows using Docker, CI/CD, artifact versioning, and automated tests.
• Implement continuous dataset and model monitoring for quality and drift.
• Maintain documentation, versioning, and traceability aligned with safety expectations.
• Guide junior engineers and interns on ML best practices.
• Collaborate with perception, systems, and test teams to ensure tool adoption and integration.
• Drive innovation by identifying ML opportunities across the ADAS test ecosystem.
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:
Skills Required
- Design and implement ML tools for scenario classification, tagging, search, anomaly detection, and sensor data quality (vision, radar, LiDAR)
- Build scalable pipelines to ingest, preprocess, and transform camera, radar, and LiDAR datasets
- Develop automated data curation workflows (filtering, clustering, stratified sampling)
- Implement model-agnostic interfaces for dataset replay in SIL/HIL environments and integrate with SIL/HIL simulation frameworks
- Create ground-truth generation tools (manual and semi-automated), sensor fusion visualization and annotation tooling
- Integrate applications into verification ecosystems (HIL benches, simulation platforms, CI/CD) and build ML modules for scenario orchestration and execution engines
- Create reproducible ML workflows using Docker, CI/CD, artifact versioning, and automated tests
- Implement continuous dataset and model monitoring for quality and drift and maintain documentation, versioning, and traceability aligned with safety expectations
- Work with system verification teams to define KPIs, metrics, and evaluation frameworks
- Guide and mentor junior engineers and interns on ML best practices
What the Team is Saying
What We Do
We are a mobility company that innovates like a start-up and thinks like a technology company. This helps us anticipate change in one of the most complex industries in the world and respond quickly. We depend on a team of 171,000 dynamic, entrepreneurial-minded employees in an environment where great ideas flourish. Our presence spans 343 manufacturing operations and 88 product development, engineering and sales centers in 29 countries. We understand that you need a career as unique as you are. Whether you want to advance your existing expertise or try something completely different, we are committed to your growth.
Why Work With Us
At Magna, our engineering team is advancing mobility for everyone and everything. Joining this team means being a part of the design, development, and manufacturing of the world’s most advanced mobility technology. Innovations that move families, shape communities, and improve lives. You can follow your passions and shape your own career path.
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Magna International Teams
Magna International Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Majority of roles are hybrid with flexibility. Please speak with our recruiting team for specific details on hybrid work.
