Working Student (m/f/x) - Radar Perception

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What we offer:

Group Summary:

About the Role

Join our Radar perception team and help build the data and algorithms behind environment perception for automated driving. You will work with real Radar and LiDAR point cloud data, develop machine learning methods for detecting drivable areas and road boundaries, and contribute to the quality of our training data. You will work closely with experienced engineers and see your results used in real projects.

Your Main Responsibilities

• Develop and evaluate machine learning models for road border and drivable free-space segmentation using LiDAR point cloud data
• Analyze model performance, identify failure cases, and propose improvements
• Create, review, and maintain high-quality annotations for LiDAR point cloud datasets
• Contribute to the development and optimization of labeling guidelines and quality assurance processes
• Support the automation of data labeling workflows
• Implement and test feature extraction methods for radar-based object classification
• Evaluate the effectiveness of extracted features for downstream machine learning tasks
• Document methods, experiments, and results in a clear and structured manner
• Present progress, findings, and recommendations in regular team meetings
• Collaborate closely with interdisciplinary teams in the fields of machine learning, perception, and autonomous driving systems

Who we are looking for

• Currently enrolled in a Bachelor’s or Master’s program in Computer Science, Electrical Engineering, Robotics, Mathematics, or a related field
• Solid programming skills in Python
• Knowledge of machine learning fundamentals (ideally with PyTorch or TensorFlow)
• Experience with point cloud processing (e.g., Open3D, PCL, NumPy)
• Good English communication skills, written and spoken
• Structured, independent working style, with attention to detail

Your preferred qualifications

• Familiarity with computer vision or deep learning for 3D data (e.g., PointNet, PointPillars, semantic segmentation)
• Experience with data labeling tools or dataset handling
• Knowledge of Git, Linux, and Docker
• Interest in autonomous driving and sensor technologies

Site Benefits

• Collegial, supportive, and friendly working atmosphere with a "Duz" culture
• Attractive and performance-oriented compensation package
• Prospects and opportunities for personal and professional development through various training offers.
• Corporate benefits program
• International and diverse environment and open-door culture

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.