Embedded AI/ML Developer

HP France

Embedded AI/ML Developer deploying optimized machine-learning models across HP commercial PCs and connected devices. Integrating inference runtimes with firmware, accelerators, sensors, and system software.

Posted 8/19/2026full-timeSpring • Texas • 🇺🇸 United StatesSeniorLead💰 $147,050 - $230,850 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing embedded AI/ML software for edge devices, with a strong focus on model deployment, performance tuning, and integration with hardware and firmware. Proficient in utilizing AI frameworks and optimization techniques to enhance system efficiency and responsiveness.

Highest-signal resume keywords

Embedded Software DevelopmentAI/ML Model DeploymentC/C++ and Python ProficiencyModel Optimization TechniquesIntegration with Embedded Firmware

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Embedded Software DevelopmentAI/ML Model DeploymentC/C++ ProgrammingPython ProgrammingModel Optimization TechniquesAI/ML FrameworksEmbedded System ArchitectureDebugging and ProfilingMachine Learning Inference PipelinesSensor Input Handling

Soft Skills

CollaborationProblem-SolvingIndependent Work

Tools & Technologies

TensorRTONNXTFLitePyTorchTensorFlowOpenVINORTOSLinuxWindowsJTAG

Industry Keywords

Embedded AIEdge InferenceAI ValidationModel BenchmarkingFirmware InterfacesCommunication ProtocolsHardware/Software Co-OptimizationMulti-Threaded DevelopmentReal-Time ExecutionCross-Functional Engineering

Tech Stack

Tools & technologies

LinuxPythonPyTorchRTOSTensorflow

About the role

Key responsibilities & impact

Design, develop, and optimize embedded AI/ML software for edge devices, including PCs, docking solutions, displays, peripherals, and other intelligent client platforms
Convert AI/ML algorithms and proof-of-concept models into efficient, production-quality embedded implementations optimized for latency, memory, power, and compute constraints
Integrate machine learning inference engines, model runtimes, and AI accelerators into embedded firmware and system software environments
Collaborate with hardware, firmware, software, and data science teams to define AI feature requirements, system architecture, data flow, model deployment strategy, and validation plans
Profile and tune embedded AI workloads to improve inference performance, reduce memory footprint, improve responsiveness, and optimize power consumption
Develop and maintain software interfaces between AI/ML components, firmware, device drivers, sensors, embedded controllers, and host applications
Support model compression, quantization, pruning, benchmarking, and deployment using embedded AI frameworks and hardware acceleration technologies
Troubleshoot complex system-level issues involving AI inference, firmware behavior, sensor data, device communication, and platform integration
Create and maintain technical documentation, including architecture descriptions, design specifications, model deployment guides, validation procedures, and integration notes
Explore emerging embedded AI, TinyML, NPU, MCU, sensor fusion, and edge inference technologies to drive innovation across future HP platforms

Requirements

What you’ll need

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
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
Strong embedded software development experience using C/C++ and Python
Experience working with sensors, camera/audio pipelines, telemetry data, wireless modules, or contextual signals
Knowledge of embedded communication protocols such as UART, I2C, SPI, USB, PCIe, Bluetooth, and Wi-Fi
Ability to read hardware specifications, device datasheets, schematics, and platform architecture documents
Proficiency in C/C++ and Python
Experience with AI/ML frameworks and formats such as PyTorch, TensorFlow, ONNX, TensorFlow Lite, and OpenVINO
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
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
Ability to work independently and collaboratively in a cross-functional engineering environment

Benefits

Comp & perks

Health insurance
Dental insurance
Vision insurance
Long term/short term disability insurance
Employee assistance program
Flexible spending account
Life insurance
4-12 weeks fully paid parental leave based on tenure
11 paid holidays
Additional flexible paid vacation and sick leave
Bonus and/or equity opportunities for United States of America candidates