Location: Kanata, Ontario, Canada
About the RoleJoin NXP's
AI & Chip Engineering (ACE) organization-one of the key hubs for
Edge AI innovation-based in Kanata. In this role, you'll contribute to the development of
embedded AI solutions powering next-generation automotive, industrial, and intelligent edge systems. You will work alongside experienced engineers to bring
machine learning models to real-world embedded platforms, focusing on performance, reliability, and scalability. This is a great opportunity to grow your expertise in
Edge AI software, embedded systems, and AI deployment workflows, while working on impactful, production-grade technologies.
What You'll Do- Develop and optimize Edge AI SW products on NXP SoCs (MCU/MPU)
- Assist in deploying machine learning models to embedded platforms with real-time constraints
- Contribute to AI inference pipelines and runtime integration
- Support performance optimization (latency, memory, power) through profiling and tuning
- Work with cross-functional teams (AI, system, and silicon teams) to integrate solutions
- Participate in the development lifecycle: implementation, testing, debugging, and validation
Core Qualifications- Bachelor's degree in Computer Science, Electrical Engineering, or a related field
- 2-5 years of experience in embedded software development (C/C++, Python)
- Familiarity with Linux-based embedded systems
- Experience with software debugging, profiling, and performance tuning
- Familiarity with AI frameworks (TensorFlow, PyTorch, ONNX, TFLite)
- Exposure to AI/ML, DSP, or computer vision algorithms (academic or industry)
- Strong problem-solving skills and attention to detail
Preferred Skills- Basic understanding of processor architecture (e.g., ARM, SIMD/NEON)
- Exposure to hardware acceleration (GPU, DSP, NPU) is a plus
- Awareness of model optimization techniques (quantization, pruning)
- Knowledge of automotive software standards (e.g., ISO 26262, AUTOSAR) is a plus
What We're Looking For- Strong interest in Edge AI and embedded systems
- Eagerness to learn and grow in AI software and system optimization
- Ability to collaborate effectively in a team environment
- Proactive attitude and willingness to take ownership of assigned tasks
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