NPU Compiler SW Engineer

Ready to join the future of innovation at NXP? NXP Semiconductors enables secure connections and infrastructure for a smarter world, advancing solutions that make lives easier, better and safer. As the world leader in secure connectivity solutions for embedded applications, we are driving innovation in the secure connected vehicle, end-to-end security & privacy and smart connected solutions markets.  Built on more than 60 years of combined experience and expertise, the company has 45,000 employees in more than 35 countries. Additional information can be found by visiting www.nxp.com . Your Responsibilities Design, develop, test, debug and optimize compiler technology for NXP NPU hardware. Collaborate with hardware and systems engineering teams to improve the performance, robustness, and ease-of-use of the software stack. Provide technical support to customers. Work with widely used discriminative and generative AI/ML models. Ensure compliance with quality and safety standards (MISRA C/C++, CERT, HIS, ASPICE). Use agentic AI tools as part of day-to-day development.   Your Team As a member of our team that develops software for ML, you will extend your practical experience on neural network architectures, model inference, optimization and deployment. As part of your daily activities you will create, test and maintain code for deploying neural networks on NXP hardware, with a focus on our proprietary neural accelerator (NPU) called Neutron, using our proprietary neural network compiler. You will work with and learn from recognized technical leaders in the ML domain. You will be part of Agile teams and you'll use state-of-the-art software lifecycle management tools while following ML software development standards. Your Profile Must have skills: BS or MS degree in Computer Science, Computer Engineering, or related degree Basic knowledge of compiler technologies Good C, C++ and Python programming skills Good knowledge of data structures and algorithms, best practices, design patterns Good knowledge of embedded systems and operating systems Good knowledge of Linux development environment Good knowledge of Machine Learning concepts: CNN, Conv2D, DepthwiseConv2D, MaxPool, AvgPool, Dense, non-linear activations, quantization Good knowledge of signal processing and common algorithms: matrix algebra, convolution, correlation, Look Up Tables Troubleshooting skills (program debugging, solve compiling issues, solve network miss configurations) Good technical presentation skills Fluency in English written and spoken   The following are pluses:    Experience with LLVM/MLIR compiler infrastructure Knowledge of transformer networks Knowledge of quality and safety standards (MISRA C/C++, CERT, HIS, ASPICE). Experience with deep learning frameworks (TensorFlow, Keras, Pytorch) and familiarity with state-of-the-art NN architectures (SSD, MobileNet, ResNet, Yolo) Experience with Agile methodology, version control…