1

Ml Inference Jobs in Houston, TX (NOW HIRING)

Embedded AI/ML Developer

Spring, TX

$117K - $154K/yr

Responsibilities include model optimization, inference runtime integration, performance tuning ... Converts AI/ML algorithms and proof-of-concept models into efficient, production-quality embedded ...

... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...

Principal AI/ML Software Engineer

Houston, TX · On-site

$128K - $172K/yr

Strong foundation in statistics, A/B testing, causal inference, and experimental design • ... ML engineering, or related roles • 3+ years building NLP/generative AI applications and ...

AI/ML Engineer - Remote

Houston, TX · Remote

$200 - $350/hr

AI/ML Engineer Job Type: Full-Time Location: Remote Job Summary We are seeking an experienced AI/ML ... for AI training and inference. * Develop and maintain REST APIs and SDK integrations

Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). A successful candidate would possess ...

Build LLM-powered solutions using prompt engineering, fine-tuning, inference optimization, and agent-based architectures. Business Decision Support * Convert statistical and ML findings into ...

AI/ML Engineer Job Type: Full-Time Location: Remote Job Summary We are seeking an experienced AI/ML ... for AI training and inference. * Develop and maintain REST APIs and SDK integrations

AI Data Engineer

Spring, TX · On-site

$101K - $122K/yr

Responsibilities : • Collaborate with data modelers to prepare and optimize datasets for AI model training and inference. • Design and implement data pipelines that support AI/ML workflows ...

Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations ... and inference efficiency to minimize cost and latency while preserving accuracy. * MLOps ...

Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...

next page

Showing results 1-20

Ml Inference information

See Houston, TX salary details

$35.8K

$117.2K

$187.7K

How much do ml inference jobs pay per year?

As of Sep 5, 2026, the average yearly pay for ml inference in Houston, TX is $117,212.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,100.00 and $129,900.00 per year, depending on experience, location, and employer.

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What are the key skills and qualifications needed to thrive in ML inference?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.

What are some common challenges faced by ML inference engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

What job categories do people searching Ml Inference jobs in Houston, TX look for?

The top searched job categories for Ml Inference jobs in Houston, TX are:

What cities near Houston, TX are hiring for Ml Inference jobs?

Cities near Houston, TX with the most Ml Inference job openings:

Embedded AI/ML Developer

Hewlett Packard Enterprise

Spring, TX • On-site

$147 - $231/hr

Other

Medical, Dental, Vision, Life, PTO

Posted 4 days ago


Hewlett Packard Enterprise rating

8.4

Company rating: 8.4 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

35th of 161 rated electronics manufacturers


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"

You want to reshape the way the world works. So do we. You’re looking for more than just a job; you’re looking to make a difference. That means creating something new. Something that matters. Something that changes how the world works for the better. A career at HP can help you build the tomorrow you want. Let’s grow together.

Privacy, Terms of Use, and Accessibility Our founders believed that business exists when people work together to ‘accomplish something collectively which they could not accomplish separately.’ We uphold a zero-tolerance policy towards discrimination and treat everyone with respect. By maintaining these principles, we empower the HP team to contribute to our collective success and the future of work. Learn more about HP personal data practices at Privacy Statement, Personal Data Rights Notice (where applicable), Accessibility at HP, and Terms. You can be yourself at HP. Learn more

#J-18808-Ljbffr

What Hewlett Packard Enterprise employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom