Machine Learning Engineer - ADAS Location: Ingolstadt, Germany Type: Contract 6 months | About the Role Join a leading semiconducotr compnay in automotive innovation. Our client has rapidly become a trusted technology leader in infotainment and autonomous driving, leveraging their expertise in mobile to disrupt the automotive space. Their Snapdragon platform is powering next-generation cockpit experiences with advanced audio, video, graphics, and AI/ML capabilities. As an ML Engineer, you'll work within the Automotive Engineering team, collaborating with global OEMs and Tier 1s from concept to commercialization. This role centers around designing and optimizing ML models for real-time embedded systems, contributing to the future of assisted and autonomous driving. What You'll Do Support end-to-end development of ML features for ADAS, from prototype to production Analyze, debug, and optimize neural networks for embedded SoCs Collaborate on the development of robust, real-time ML pipelines for perception tasks Use tools and frameworks such as TensorFlow, PyTorch, OpenCV, OpenCL Perform model compression, pruning, quantization, and runtime optimization Drive system-level integration with embedded platforms (Linux, QNX, Android) Contribute to technical design discussions and mentor junior engineers Participate in cross-functional efforts with BSP, vision, and safety teams What You Bring Strong software development or application engineering background Proficiency in C/C++ and modern scripting (e.g. Python) Deep understanding of ML/DL architectures (CNNs, etc.) and computer vision Experience with embedded execution of neural networks and system-level optimization Solid grasp of matrix operations, quantization, and model transformation Experience with debugging and performance tuning of ML pipelines Comfortable working with embedded operating systems (Linux, QNX, Android) Excellent problem-solving, analytical, and teamwork skills Structured working style and ability to lead small project teams Preferred Skills Prior experience with automotive ML, ADAS, or infotainment projects Hands-on with ML accelerators and embedded inference engines Familiar with MLPerf or similar benchmarking tools Experience with data pipelines and real-time video/image processing Knowledge of automotive software standards (e.g. ISO 26262, ASPICE) is a plus Education Bachelor's or Master's degree in Computer Science, Engineering, Electronics, or related field