Summary: NXP is seeking AI Engineers to design, develop, and optimize model-zoo infrastructure for next-generation computer vision, generative AI, and LLM workloads. Highlights: 1. Contribute to cutting-edge technologies and grow technical depth 2. Hands-on experience with AI accelerator hardware and SDKs 3. Opportunity to work with a wide range of customer models Job Title: **AI Software Engineer** Company: **NXP Semiconductors México, S. de R.L. de C.V.** NXP offers an inclusive, collaborative, and innovation\-driven work culture where engineers have the freedom to explore ideas, contribute to cutting\-edge technologies, and grow their technical depth. Job Summary As part of ongoing enhancements to our **Discrete NPU Model Zoo** , we are looking for AI Engineers to contribute to the design, development, and optimization of model ‑ zoo infrastructure supporting next ‑ generation **computer vision** , **generative AI** , and **LLM workloads** . You will work on developing compilation, inference, and performance workflows for AI accelerators, while helping build end ‑ to ‑ end demos and benchmarking pipelines. CNN Model Zoo Responsibilities * Collaborate on scaling up our CNN ‑ based model zoo. * Add new models and their variants in both Python and C\+\+. * Improve accuracy across \~50 existing models. * Re ‑ implement variant models in PyTorch for integration with the MCW tool. * Use the MCW tool for optimization, pruning, and performance tuning. * Automate model testing, validation, and optimization flows where feasible. * Develop gstreamer / NXP nnstreamer plugins and end ‑ to ‑ end inference pipelines. * Build high ‑ quality demos showcasing model capabilities on NPU accelerators. LLM/VLM Model Zoo Responsibilities * Contribute to the development and expansion of the LLM model zoo. * Use Hugging Face APIs to build required pipelines and workflows (Python and C\+\+). * Integrate and support multiple variants of LLMs and VLMs. * Develop automated testing frameworks and Jenkins ‑ based CI pipelines. * Execute benchmarking, performance profiling, and validation of LLM/VLM models. * Build demos demonstrating large ‑ model capabilities on our NPU platforms. Job Qualifications * Bachelor’s degree in Electronics/Computer/Systems/Robotics Engineering or similar with **3\+ years of experience** in Machine Learning or related fields. * Strong proficiency in **Python** (AI scripting \& workload automation) and **C/C\+\+** (low ‑ level performance work). * Solid understanding of **deep learning architectures** across CV, NLP, or generative models. * Experience building **demos/applications** using **CNN** and **LLM** models. * Ability to measure and report **latency, throughput, accuracy, and power** for AI workloads. * Familiarity with **LLM benchmarking** frameworks such as **MMLU, HumanEval, GSM8K, ARC Challenge, GPQA** , etc. * Experience working with **Hugging Face APIs** , model repositories, and deployment workflows. * Knowledge of **Linux environments** , build systems, and optionally, driver ‑ level basics. * Experience with **GitHub** , CI/CD pipelines, and automated testing frameworks. * Fluency in English (written and spoken) is required. Preferred Qualifications * Experience with **NPU architectures** , compiler toolchains, and runtime environments. * Exposure to a variety of **AI/ML/DL frameworks** such as **TensorFlow, PyTorch, Caffe** , and ONNX pipelines. * Strong skills in developing AI workflows in both **C\+\+ and Python** . * Experience in **hardware/software performance evaluation** and profiling. * Ability to work effectively both **independently** and in **collaborative team settings** . * Strong aptitude for learning new tools, technologies, and AI workflows quickly. What You Will Gain * Hands ‑ on experience with **AI accelerator hardware** , **NXP SDKs** , and next ‑ generation AI solutions. * Opportunity to work with a wide range of customer models across **CV, LLM, VLM** , and Generative AI domains. * Deep exposure to end ‑ to ‑ end AI pipelines, benchmarking methodologies, and model ‑ zoo development. * Learning environment focused on innovation, performance optimization, and practical deployment of AI workloads. \#LI\-FCC3 More information about NXP in Mexico... \#LI\-fcc3