Job description

Job Responsibilities: Define and maintain the NPU software product roadmap spanning the full stack: AI/ML compiler pipeline, AI/ML tools for optimization (conversion, quantization, pruning), runtime and execution engine, SDK and developer APIs, model optimization, workflow and repository, and existing eIQ platform integration. Own and create a scalable platform/toolkit to support newer model architectures (CNNs, LLMs, ViTs, VLMs) and enable a path to Day 0 model support in the long run. Maintain familiarity with supported architectures and operators, align customer expectations with available model support, and work with Engineering to close identified gaps. Engage closely with GTM to help prioritize industry verticals, segments, and use cases to create an enablement strategy for all business units. Enable system-level solutions through pre-sales and sales strategy and support. Define an integrated compiler strategy and transition all NXP AI products to a unified AI workflow across business units. Continuously monitor AI market developments and trends (compilers, operators, frameworks, models, microservices, skills, and agents) and build or refine NXP’s AI strategy. Drive the eIQ integration strategy—integrate the current- and next-generation Neutron compiler and SDK within NXP s eIQ developer environment and define NPU support for the existing MPU/MCU developer base. Create a cradle-to-grave plan for features and components during eIQ integration. Develop use-case-driven software enablement and help prioritize, reset, and reconcile existing features to deliver a holistic user experience. Own the upstream open-source compiler integration strategy—define NXP s participation and contribution roadmap for Apache TVM, MLIR/LLVM, ONNX Runtime, and PyTorch/TensorFlow export paths. Define and maintain the model zoo or an equivalent—curate, compile, quantize, and benchmark frontier models (LLaMA variants, YOLO generations, Whisper, Phi, Gemma, custom vision transformers) on Ara NPU and publish validated results. Own the developer experience end-to-end: SDK installation, model import workflow, compilation, profiling, debugging, and deployment—define and track developer adoption funnel metrics. Manage framework and ISV partner relationships—PyTorch, TensorFlow, Hugging Face, ONNX Runtime, and key vertical AI software partners; drive NPU support contributions and co-marketing. Support external software integrations and licensing partnerships. Run beta and early-access programs with strategic developer customers; translate feedback into prioritized engineering requirements. Define software versioning policy, backward compatibility commitments, and long-term support (LTS) release strategy. Own competitive benchmarking of model coverage against Qualcomm AI Hub, DeepX, Axelera Metis SDK, and Arm NN/ExecuTorch while preserving software ease of use. Maintain a working knowledge of firmware and PCIe and USB drivers. undefined Develop end-to-end system software solutions and demonstration platforms for hardware and software developers at industry events and conferences. Job Qualifications: 8 years of AI product management experience in software, developer tools, or AI/ML infrastructure, with direct ownership of a software product roadmap and developer-facing API surface. Strong understanding of the inference model deployment pipeline—training frameworks (PyTorch, TensorFlow), model exchange formats (ONNX, TFLite), and inference runtime environments. Familiarity with compiler toolchain concepts: graph optimization, operator fusion, quantization, and code generation—sufficient to write actionable requirements and evaluate engineering tradeoffs. Experience defining and tracking developer adoption metrics—SDK downloads, model compilations, active deployments, and support ticket analysis. Track record of driving open-source or partner ecosystem strategy—upstream contributions, ISV enablement, or developer community programs. Strong prioritization discipline—experience managing a large backlog across multiple engineering teams with competing priorities. Excellent technical communication skills; able to write a developer-facing API specification and an executive strategy memo in the same week. Good to have: Direct experience with MLIR, TVM, ONNX Runtime, or other open-source ML compiler frameworks. Hands-on experience with model quantization—INT8/INT4/FP16, calibration workflows, and accuracy validation. Background in NPU, GPU, or inference accelerator software stacks—Qualcomm SNPE/QNN, Hailo Dataflow Compiler, TensorRT, Core ML, or equivalent. Experience with heterogeneous execution environments—managing workload dispatch across CPU, GPU, and dedicated accelerators. Familiarity with embedded Linux, Android, or RTOS software environments for edge deployment. Understanding of automotive software standards, including AUTOSAR and ASPICE, as well as functional safety and security, is a plus for MCU and MPU alignment. MBA or advanced degree in computer science, electrical engineering, or a related discipline. More information about NXP in the United States... NXP is an Equal Opportunity/Affirmative Action Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, NXP will provide reasonable accommodations for otherwise qualified disabled individuals. #LI-6692

Requirements

Must-haves

Own and create a scalable platform/toolkit to support newer model architectures (CNNs, LLMs, ViTs, VLMs) and enable a path to Day 0 model support in the long run.
Maintain familiarity with supported architectures and operators, align customer expectations with available model support, and work with Engineering to close identified gaps.
Engage closely with GTM to help prioritize industry verticals, segments, and use cases to create an enablement strategy for all business units.
Enable system-level solutions through pre-sales and sales strategy and support.
Define an integrated compiler strategy and transition all NXP AI products to a unified AI workflow across business units.
Continuously monitor AI market developments and trends (compilers, operators, frameworks, models, microservices, skills, and agents) and build or refine NXP’s AI strategy.
Develop use-case-driven software enablement and help prioritize, reset, and reconcile existing features to deliver a holistic user experience.
Own the upstream open-source compiler integration strategy—define NXP s participation and contribution roadmap for Apache TVM, MLIR/LLVM, ONNX Runtime, and PyTorch/TensorFlow export paths.
Own the developer experience end-to-end: SDK installation, model import workflow, compilation, profiling, debugging, and deployment—define and track developer adoption funnel metrics.
Run beta and early-access programs with strategic developer customers; translate feedback into prioritized engineering requirements.
Define software versioning policy, backward compatibility commitments, and long-term support (LTS) release strategy.
Own competitive benchmarking of model coverage against Qualcomm AI Hub, DeepX, Axelera Metis SDK, and Arm NN/ExecuTorch while preserving software ease of use.
Maintain a working knowledge of firmware and PCIe and USB drivers.
Develop end-to-end system software solutions and demonstration platforms for hardware and software developers at industry events and conferences.
8 years of AI product management experience in software, developer tools, or AI/ML infrastructure, with direct ownership of a software product roadmap and developer-facing API surface.
Strong understanding of the inference model deployment pipeline—training frameworks (PyTorch, TensorFlow), model exchange formats (ONNX, TFLite), and inference runtime environments.
Familiarity with compiler toolchain concepts: graph optimization, operator fusion, quantization, and code generation—sufficient to write actionable requirements and evaluate engineering tradeoffs.
Experience defining and tracking developer adoption metrics—SDK downloads, model compilations, active deployments, and support ticket analysis.
Track record of driving open-source or partner ecosystem strategy—upstream contributions, ISV enablement, or developer community programs.
Strong prioritization discipline—experience managing a large backlog across multiple engineering teams with competing priorities.
Excellent technical communication skills; able to write a developer-facing API specification and an executive strategy memo in the same week.
Direct experience with MLIR, TVM, ONNX Runtime, or other open-source ML compiler frameworks.
Hands-on experience with model quantization—INT8/INT4/FP16, calibration workflows, and accuracy validation.

Nice-to-haves

Understanding of automotive software standards, including AUTOSAR and ASPICE, as well as functional safety and security, is a plus for MCU and MPU alignment.

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Platform: workday
Effort: long

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