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 LI-f35f