Edge AI/ML Engineer for Embedded Systems

Hewlett Packard Enterprise; Spring (TX); Hybrid; USD 147,000 - 231,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Disability insurance

Employee assistance program

Flexible spending account

Life insurance

Parental leave

Paid holidays

Flexible vacation and sick leave

Job summary

Hewlett Packard Enterprise seeks an Embedded AI/ML Developer to design, develop and optimize AI‑enabled embedded software for HP’s commercial PC and connected device portfolio. This role focuses on deploying efficient models at the edge, integrating AI into firmware and system software, and enabling intelligent user experiences on resource‑constrained platforms.

The engineer will work with hardware, firmware, software and data science teams to translate AI/ML concepts into production‑ready

Qualifications

• Bachelor’s or Master’s degree in CS/CE/Stats/Math/AI/ML/Robotics or related field.
• 7–10 years of relevant embedded software, firmware, AI/ML deployment, edge inference.
• Strong C/C++ and Python; experience with embedded platforms and AI toolchains.

Responsibilities

• Design, develop, and optimize embedded AI/ML software for edge devices.
• Integrate AI inference engines and accelerators into firmware and system software.
• Profile and tune AI workloads for latency, memory, and power constraints.
• Collaborate with cross‑functional teams to define AI feature requirements and validation plans.
• Document architecture, design specifications and deployment guides.

Skills

C/C++

Python

Embedded systems

Edge AI

Model deployment

Firmware integration

Performance optimization

Education

Bachelor’s or Master’s in CS/CE/Stats/Math/AI/ML/Robotics

Tools

TensorRT

ONNX

TensorFlow Lite

PyTorch

OpenVINO

Job description

Hewlett Packard Enterprise seeks an Embedded AI/ML Developer to design, develop and optimize AI‑enabled embedded software for HP’s commercial PC and connected device portfolio. This role focuses on deploying efficient models at the edge, integrating AI into firmware and system software, and enabling intelligent user experiences on resource‑constrained platforms.

The engineer will work with hardware, firmware, software and data science teams to translate AI/ML concepts into production‑ready