Embedded AI/ML Developer

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

Embedded AI/ML Developer Description - The Embedded AI/ML Developer will design, develop, and optimize AI-enabled embedded software solutions for HP’s commercial PC and connected device portfolio. This role focuses on deploying efficient machine learning models at the edge, integrating AI capabilities with firmware and system software, and enabling intelligent user experiences across resource‑constrained platforms. The engineer will work closely with hardware, firmware, software, and data science teams to translate AI/ML concepts into production‑ready embedded implementations.

Responsibilities including model optimization, inference runtime integration, performance tuning, debugging, documentation, and staying current with emerging edge AI technologies, tools, and industry best practices.

Responsibilities Designs, develops, and optimizes embedded AI/ML software for edge devices, including PCs, docking solutions, displays, peripherals, and other intelligent client platforms. Converts AI/ML algorithms and proof‑of‑concept models into efficient, production‑quality embedded implementations optimized for latency, memory, power, and compute constraints. Integrates machine learning inference engines, model runtimes, and AI accelerators into embedded firmware and system software environments. Collaborates with cross‑functional teams to define AI feature requirements, system architecture, data flow, model deployment strategy, and validation plans. Profiles and tunes embedded AI workloads to improve inference performance, reduce memory footprint, improve responsiveness, and optimize power consumption. Develops and maintains software interfaces between AI/ML components, firmware, device drivers, sensors, embedded controllers, and host applications. Supports model compression, quantization, pruning, benchmarking, and deployment using embedded AI frameworks and hardware acceleration technologies. Troubleshoots complex system‑level issues involving AI inference, firmware behavior, sensor data, device communication, and platform integration. Creates and maintains technical documentation, including architecture descriptions, design specifications, model deployment guides, validation procedures, and integration notes. Explores emerging embedded AI, TinyML, NPU, MCU, sensor fusion, and edge inference technologies to help drive innovation across future HP platforms.

Education & Experience Recommended Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Statistics, Mathematics, Artificial Intelligence, Machine Learning, Robotics or a related technical discipline. 7–10 years of relevant experience in embedded software, firmware, AI/ML deployment, edge inference, or system‑level software development.

Preferred Certifications

• Embedded AI/ML Engineering Hands‑on experience deploying AI/ML models on embedded systems, edge devices, MCUs, SoCs, NPUs, DSPs, or other constrained compute platforms.
• Experience with model optimization techniques such as quantization, pruning, compression, TensorRT, ONNX, TFLite, or similar deployment toolchains.
• Strong understanding of ML inference pipelines, data preprocessing, sensor input handling, feature extraction, and runtime performance tuning.
• Experience integrating AI workloads with embedded firmware, device drivers, RTOS, Linux, Windows, or low‑level system software environments.
• Familiarity with AI validation, automated testing, CI/CD pipelines, model benchmarking, and regression testing for embedded platforms.

Embedded Systems and Platform Integration Strong embedded software development experience using C/C++ and Python for prototyping, automation, model conversion, and testing. Experience working with sensors, camera/audio pipelines, telemetry data, wireless modules, or contextual signals used by AI‑enabled experiences. Knowledge of embedded communication protocols such as UART, I2C, SPI, USB, PCIe, Bluetooth, Wi‑Fi, or other device interconnect standards. Ability to read hardware specifications, device datasheets, schematics, and platform architecture documents to support AI/ML feature integration.

Knowledge & Skills

• Proficient in C/C++ and Python; familiar with embedded scripting, automation, build systems, and model deployment workflows.
• Experience with AI/ML frameworks and formats such as PyTorch, TensorFlow, ONNX, TensorFlow Lite, OpenVINO, or similar toolchains.
• Knowledge of embedded system architecture, boot flow, firmware interfaces, memory constraints, power management, and real‑time execution tradeoffs.
• Skilled in embedded debugging and profiling using JTAG, SWD, logic analyzers, oscilloscopes, performance counters, tracing tools, or vendor‑specific debug environments.
• Experience optimizing AI workloads for latency, throughput, memory footprint, thermal behavior, and battery life on constrained devices.
• Familiarity with AI accelerator SDKs, NPU/DSP/GPU offload, heterogeneous compute, and hardware/software co‑optimization.
• Understanding of RTOS concepts, Linux/Windows system software, multi‑threaded development, secure update mechanisms, and production‑quality embedded software practices.
• Strong analytical and problem‑solving skills with the ability to debug complex interactions across model behavior, firmware, drivers, sensors, and host software.
• Ability to work independently and collaboratively in a cross‑functional engineering environment, translating AI concepts into reliable product experiences.

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• Long term/short term disability insurance
• Employee assistance program
• Flexible spending account
• Life insurance
• Generous time off policies, including
• 4-12 weeks fully paid parental leave based on tenure
• 11 paid holidays
• Additional flexible paid vacation and sick leave (US benefits overview)

The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job‑related knowledge, skills, and experience. The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law.

Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation

Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP’s EEO Policy or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal"

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