Maharashtra, IN
Open 4 months, first seen by us 123 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Design and implement ML tools for scenario tagging, search and anomaly detection
Create scalable pipelines for camera, radar and LiDAR data
Build ML modules that plug into SIL/HIL simulation and CI/CD pipelines
Develop ground truth generation and sensor fusion annotation tools
Guide junior engineers and interns on ML best practices
Design and implement ML based tools for:
Create scalable pipelines to ingest, preprocess, and transform camera, radar, and LiDAR datasets.
Build ML modules that plug into:
Develop applications for:
Guide junior engineers and interns on ML best practices.
From the employer’s posting.
Open 4 monthsWe first saw this posting 123 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 123
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past Magna International’s usual: its jobs come down by about day 50.
From 5,460 similar postings that came down, and 21 of Magna International’s. Coming down is not always a hire.
16 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
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. Awareness, Unity, Empowerment:
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job descriptions may display in multiple languages based on your language selection.
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.
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Maharashtra, IN
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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