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Working Student (f/m/d) AI for Radar Perception

NXP Semiconductors

NXP Semiconductors

Software Engineering, Data Science
Hamburg, Germany
Posted on Jul 8, 2025

About Us
At NXP Semiconductors, our Radar Architecture team develops advanced AI-driven radar solutions to enable intelligent perception for next-generation automotive applications. We work across the stack—from low-level radar signal understanding to multi-sensor (camera + radar) scene perception—always with a strong link to embedded deployment and real-world use cases. Our work supports production-level systems in partnership with major Tier-1s like CARIAD, Aptiv, and Continental.

Key Responsibilities

  • Assist in developing and evaluating computer vision models for scene understanding using radar and camera inputs

  • Develop data pre-processing algorithms for training and validation

  • Support the implementation of radar-camera fusion pipelines using PyTorch

  • Run model experiments on embedded platforms and analyze performance metrics

  • Help visualize outputs in Bird’s Eye View (BEV), image, or 3D voxel spaces

  • Collaborate with cross-functional teams and contribute to technical discussions

What We’re Looking For

  • Currently pursuing a Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field

  • Experience with PyTorch or TensorFlow for training deep learning models

  • Familiarity with basic radar signal processing or computer vision

  • Interest in embedded AI and multi-modal perception

  • Strong Python skills and motivation to contribute to real-world ML systems

Bonus Points

  • Familiarity with deployment tools such as TensorRT, TVM, or OpenCL

  • Experience with large-scale datasets like nuScenes, Waymo Open Dataset, or K-Radar

  • Exposure to 3D vision or volumetric methods for scene understanding

Why Join Us?

  • Contribute to industry-relevant projects in radar perception and fusion

  • Gain hands-on experience with embedded AI in a production context

  • Work alongside experts in signal processing, hardware, and machine learning

  • Flexible hours and hybrid work setup to support your academic schedule

More information about NXP in Germany...

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