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Openvino Jobs in Spring, TX (NOW HIRING)

Embedded AI/ML Developer

Spring, TX

$117K - $154K/yr

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 ...

Openvino information

What is OpenVINO?

OpenVINO (Open Visual Inference and Neural Network Optimization) is a free toolkit developed by Intel to help developers optimize and deploy AI inference, particularly deep learning models, across Intel hardware such as CPUs, GPUs, VPUs, and FPGAs. It is mainly used for accelerating computer vision applications like image classification, object detection, and facial recognition. OpenVINO streamlines the process of converting and optimizing models from popular frameworks, making them faster and more efficient for edge and cloud deployments.

What skills and qualifications are needed to work with OpenVINO?

To thrive as an OpenVINO Developer, you need a solid background in computer vision, deep learning, and proficiency in Python or C++, often supported by a degree in computer science or a related field. Familiarity with the OpenVINO toolkit, neural network optimization, and frameworks like TensorFlow or PyTorch is essential. Strong problem-solving skills, attention to detail, and effective communication help developers collaborate and innovate in deploying AI solutions. These skills ensure optimized AI performance on edge devices and successful integration of machine learning models into production environments.

What challenges do professionals face when deploying AI models to edge devices using OpenVINO?

Professionals working with OpenVINO often encounter challenges related to optimizing and converting AI models to ensure they run efficiently on diverse edge hardware. These challenges include ensuring compatibility with various device architectures, minimizing inference latency, and handling limitations in memory and compute resources. Additionally, troubleshooting model conversion errors and maintaining accuracy during optimization are frequent tasks. Collaboration with hardware engineers and software developers is also essential to address performance bottlenecks and integrate solutions smoothly into production environments.

What is the difference between Openvino vs Computer Vision Engineer?

AspectOpenvinoComputer Vision Engineer
Required CredentialsKnowledge of AI frameworks, hardware optimization, programming skillsDegree in Computer Science, Electrical Engineering, or related fields; experience in AI and image processing
Work EnvironmentTech companies, AI development labs, hardware manufacturersResearch institutions, tech firms, startups, or industry-specific companies
Employer & Industry UsagePrimarily used in AI inference optimization, embedded systems, and hardware accelerationDeveloping and implementing computer vision algorithms for applications like surveillance, robotics, and autonomous vehicles

Openvino focuses on optimizing AI inference workloads and hardware acceleration, often requiring knowledge of AI frameworks and hardware. In contrast, a Computer Vision Engineer designs and develops vision algorithms, working across various industries. While both roles involve AI and image processing, Openvino is more specialized in deployment and optimization, whereas Computer Vision Engineers focus on algorithm development and application.

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The top searched job categories for Openvino jobs in Spring, TX are:

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Cities near Spring, TX with the most Openvino job openings:

Infographic showing various Openvino job openings in Spring, TX as of August 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Remote job distribution.

$117K - $154K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Posted 9 days ago


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 include 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.

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.
Benefits:
HP offers a comprehensive benefits package for this position, including:
  • 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 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"