Edge & Physical AI Product Manager/Director

NXP Semiconductors

. Define and maintain the NPU software product roadmap spanning the AI/ML compiler pipeline, optimization tools, runtime and execution engine, SDK and developer APIs, model optimization, workflow and repository, and eIQ platform integration.

Posted 10/13/2026full-timeUnited StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI product management with a focus on software product roadmaps, developer tools, and AI/ML infrastructure. Proficient in managing developer-facing APIs and driving open-source strategies while ensuring a seamless developer experience.

Highest-signal resume keywords

AI Product ManagementDeveloper ToolsInference Model DeploymentOpen-Source StrategyTechnical Communication

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AI/ML InfrastructureSoftware Product RoadmapDeveloper-Facing APIGraph OptimizationQuantizationModel CompilationSDK Adoption MetricsINT8 QuantizationFP16 QuantizationNPU Software Stacks

Soft Skills

Technical CommunicationCollaborationStrategic Thinking

Tools & Technologies

PyTorchTensorFlowONNXMLIRTVMApache TVMONNX RuntimeHeterogeneous Execution EnvironmentsEmbedded LinuxAndroid

Certifications & Qualifications

MBAAdvanced Degree in Computer ScienceAdvanced Degree in Electrical Engineering

Industry Keywords

AI StrategyDeveloper ExperienceEcosystem StrategyFunctional SafetySecurity

Tech Stack

Tools & technologies

AndroidApacheLinuxPyTorchRTOSTensorflow

About the role

Key responsibilities & impact

Define and maintain the NPU software product roadmap spanning the AI/ML compiler pipeline, optimization tools, runtime and execution engine, SDK and developer APIs, model optimization, workflow and repository, and eIQ platform integration.
Create a scalable platform/toolkit supporting CNN, LLM, ViT, and VLM architectures, with a long-term path to Day 0 model support.
Align customer expectations with supported model architectures and operators, and work with Engineering to close gaps.
Partner with GTM to prioritize industry verticals, segments, and use cases and create enablement strategies.
Enable system-level solutions through pre-sales and sales strategy support.
Define an integrated compiler strategy and transition NXP AI products to a unified AI workflow.
Monitor AI market developments and refine NXP’s AI strategy.
Drive eIQ integration of the Neutron compiler and SDK, define NPU support for the MPU/MCU developer base, and create cradle-to-grave integration plans.
Develop use-case-driven software enablement and prioritize and reconcile features for a holistic user experience.
Own upstream open-source compiler integration strategy for Apache TVM, MLIR/LLVM, ONNX Runtime, and PyTorch/TensorFlow export paths.
Define and maintain a model zoo; curate, compile, quantize, and benchmark models on Ara NPU and publish validated results.
Own the end-to-end developer experience from SDK installation and model import through compilation, profiling, debugging, and deployment; track adoption funnel metrics.
Manage framework and ISV partner relationships, drive NPU support contributions and co-marketing, and support external integrations and licensing partnerships.
Run beta and early-access programs with strategic developer customers and translate feedback into engineering requirements.
Define software versioning, backward compatibility, and long-term support release strategies.
Own competitive benchmarking against Qualcomm AI Hub, DeepX, Axelera Metis SDK, and Arm NN/ExecuTorch.
Maintain working knowledge of firmware, PCIe, and USB drivers.
Develop end-to-end system software solutions and demonstration platforms for hardware and software developers at industry events and conferences.

Requirements

What you’ll need

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, including PyTorch, TensorFlow, ONNX, and TFLite.
Familiarity with compiler toolchain concepts: graph optimization, operator fusion, quantization, and code generation.
Experience defining and tracking developer adoption metrics, including SDK downloads, model compilations, active deployments, and support ticket analysis.
Track record of driving open-source or partner ecosystem strategy, including upstream contributions, ISV enablement, or developer community programs.
Experience managing a large backlog across multiple engineering teams with competing priorities.
Excellent technical communication skills, including writing developer-facing API specifications and executive strategy memos.
Good to have: direct experience with MLIR, TVM, ONNX Runtime, or other open-source ML compiler frameworks.
Good to have: hands-on experience with INT8, INT4, FP16 quantization, calibration workflows, and accuracy validation.
Good to have: background in NPU, GPU, or inference accelerator software stacks such as Qualcomm SNPE/QNN, Hailo Dataflow Compiler, TensorRT, or Core ML.
Good to have: experience with heterogeneous execution environments across CPU, GPU, and dedicated accelerators.
Good to have: familiarity with embedded Linux, Android, or RTOS software environments.
Good to have: understanding of AUTOSAR, ASPICE, functional safety, and security.
MBA or advanced degree in computer science, electrical engineering, or a related discipline is a plus.