Edge AI Model Optimization Software Engineer

What You'll Do

• in everything we do, where every point of view is valued.
• Join us! Job Summary We are looking for a hands-on AI Optimization Engineer who thrives at the intersection of algorithms, systems engineering, and production-grade software.
• We are looking for someone who wants to work at the heart of state-of-the-art AI, not yesterday’s models, but the frontier: Generative AI, Transformers, Vision-Language Models (VLMs), and the emerging wave of Agentic AI systems.
• In this role, you will contribute to the engineering of the core optimization technology that makes these advanced models run efficiently on NXP’s next-generation edge platforms, such as Ara 2.
• While Neural Network Quantization will be your primary focus, your impact will go far beyond it.
• You will architect high-performance software and collaborate across compiler, and hardware teams.
• Your work will directly define how frontier AI models are executed on-device, enabling fast, reliable, and power-efficient GenAI on resource-constrained platforms.
• If you want to work where AI innovation meets real-world engineering, and build the infrastructure that defines what tomorrow’s smart, autonomous, AI-powered devices can do, this is the role for you.
• Job Responsibilities 1.
• Optimization Tools: Own and evolve our production-grade optimization tools.
• You will design and implement quantization features, including mixed-precision flows that are robust enough for global deployment. 2.
• Pipelines: Design and maintain scalable PTQ (Post-Training Quantization) and QAT (Quantization-Aware Training) workflows, ensuring seamless integration with other optimizations and downstream deployment stacks. 3.
• Applied Innovation & Tooling: Collaborate on Proof‑of‑Concepts (POCs) for state-of-the-art quantization techniques.
• You won’t just prototype; you will evaluate the real-world impact of novel ideas and engineer the "bridge" that turns successful experiments into production-ready deployment recipes and developer tooling. 4.
• Numerical & Hardware Rigor: Apply your math foundation to implement approximation algorithms (range estimation, bias correction, BN-folding) while ensuring bit-exactness on target hardware.
• You will bridge the gap between abstract math and physical constraints like accumulator widths, saturation, and rounding behaviors. 5.
• Systems Performance: Profile and optimize the "hot paths" of our optimization toolchain to meet strict memory and compute-constrained targets. 6.
• Cross-Functional Leadership: Act as the technical bridge between AI Research and Hardware Engineering, providing quantified guidance on how choices impact model accuracy and performance. 7.
• Deployment Architecture: Document algorithmic tradeoffs and derive "gold-standard" deployment recipes, acting as technical mentor for other engineering teams, ensuring deployment strategies are scalable and repeatable.
• Job Qualifications Required Background · Education: MSc or Ph.D. (is a plus) in Computer Science, Electrical Engineering, or Mathematics with a specialization in Machine Learning or Deep Learning. · Systems Programming: Mastery of Python and C/C++.
• You should be comfortable with memory management and understanding how code maps to hardware (CPUs/NPUs). · AI Expertise: Proven experience in AI/ML with a good understanding of CNN architectures and Generative AI (Transformers). · AI Optimization: Experience with (or a strong desire to learn) quantization workflows and troubleshooting accuracy regressions. · Technical Stack: Strong hands-on experience with PyTorch, ONNX, and other AI/ML frameworks.
• Preferred · Hardware Acceleration: Experience with hardware accelerators, device-level profiling, and diagnosing memory bottlenecks. · Embedded Mindset: Familiarity with the constraints of embedded systems (latency, power, memory bandwidth). · Advanced AI: Experience implementing state-of-the-art quantization for generative AI (e.g., GPTQ, Smoothquant, etc). · Compilers: Knowledge of MLIR or TVM is a significant plus.
• What You Will Gain · Be part of a pioneering team shaping the future of AI and edge computing. · Work on innovative projects that solve real-world challenges. · Opportunity to grow with a dynamic, forward-thinking company. · Competitive salary, benefits, and a collaborative work environment. #LI-FCC3 More information about NXP in Mexico... #LI-fcc3