Location: Kanata, Ontario, Canada

About the Role

Join NXP’s AI & Chip Engineering (ACE) organization—one of the company’s flagship hubs for Edge AI innovation—based in Kanata. You’ll work at the forefront of embedded AI, enabling next-generation agentic AI, generative AI, and machine learning workloads on automotive and edge platforms. Your contributions will directly power intelligent systems across automotive, robotics, and industrial applications—where real-time, reliable AI matters. This role focuses on translating advanced AI models into optimized, production-grade embedded solutions, driving performance, efficiency, and scalability on NXP silicon.

What You’ll Do

• Design, develop, and optimize high-performance Edge AI software for NXP embedded SoCs (MCU/MPU/NPU)

• Enable deployment of machine learning and generative AI models, build and integrate AI runtimes, inference engines, and model pipelines for real-time execution

• Drive performance optimization (latency, memory, power) through low-level system tuning

• Collaborate across system, silicon, and AI teams to deliver end-to-end AI solutions

• Participate in the full lifecycle: architecture → implementation → validation → production

• Contribute to next-gen Edge AI frameworks and platform enablement

Core Qualifications

• Bachelor’s (minimum) or Master’s/PhD in Computer Science, Electrical Engineering, or related field and 10+ years of overall experience

• 3+ years of experience in embedded software development (C/C++, Python)

• Strong experience with Linux-based embedded systems and performance-critical applications

• Understanding of processor architectures (ARM, SIMD/NEON, GPU/NPU acceleration)

• Experience with AI frameworks (TensorFlow, PyTorch, ONNX Runtime, LiteRT) or custom runtimes, implementing or deploying AI/ML, DSP, or computer vision algorithms

• Proven track record in system-level optimization (CPU, memory, I/O, vectorization)

• Strong debugging, profiling, and analytical skills

Preferred Skills

• Familiarity with hardware acceleration and offload (OpenCL, CUDA, DSP toolchains)

• Experience with model optimization techniques (quantization, pruning, graph optimization)

• Knowledge of automotive standards (ISO 26262, Automotive SPICE, AUTOSAR, MISRA)

• Exposure to Edge AI deployment pipelines and benchmarking methodologies

What Sets You Apart

• Passion for bringing AI to real-world embedded systems

• Ability to operate across software, hardware, and AI domains

• Strong ownership mindset with the ability to lead technical initiatives

• Collaborative and proactive approach in cross-functional environments

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