Edge AI/ML Engineer for Embedded Systems

HP Inc.; Spring (TX); On-site; 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 (4–12 weeks)

Job summary

HP Inc. is seeking an Embedded AI/ML Developer to design, develop, and optimize AI-enabled embedded software for our commercial PC and connected device portfolio.

This role focuses on deploying efficient ML models at the edge, integrating AI with firmware and system software to enable intelligent user experiences on resource-constrained platforms. You will collaborate with hardware, firmware, software, and data science teams to translate AI concepts into production-ready embedded

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Statistics, Mathematics, AI, ML, Robotics or related field.
• 7–10 years of relevant embedded software, firmware, AI/ML deployment, edge inference, or system-level software development.

Responsibilities

• Designs, develops, and optimizes embedded AI/ML software for edge devices and PCs.
• Converts AI/ML algorithms into efficient embedded implementations optimized for latency and memory.
• Integrates inference engines and AI accelerators into firmware and system software.
• Profiles and tunes AI workloads to improve performance and power efficiency.
• Develops interfaces between AI components, firmware, device drivers, and host applications.

Skills

C/C++

Python

Edge AI

Embedded debugging

RTOS

Linux

Windows

TensorRT

ONNX

Model deployment

Education

Bachelor’s or Master’s degree in CS/CE/AI

Tools

TensorRT

ONNX

Job description

HP Inc. is seeking an Embedded AI/ML Developer to design, develop, and optimize AI-enabled embedded software for our commercial PC and connected device portfolio.

This role focuses on deploying efficient ML models at the edge, integrating AI with firmware and system software to enable intelligent user experiences on resource-constrained platforms. You will collaborate with hardware, firmware, software, and data science teams to translate AI concepts into production-ready embedded