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Edge Ai Machine Learning Jobs in Texas (NOW HIRING)

In this role, the AI & Decision Intelligence Director establishes and scales AI, machine learning, predictive analytics, and intelligent automation capabilities within Revenue Intelligence. The role ...

New

In this role, the AI & Decision Intelligence Director establishes and scales AI, machine learning, predictive analytics, and intelligent automation capabilities within Revenue Intelligence. The role ...

New

Explore and Apply Cutting-Edge ML Techniques: Stay up to date with advancements in deep learning ... generative AI. * At least three years of experience developing neural network-based algorithms ...

... Edge ML Techniques: Stay up to date with advancements in deep learning and experiment with novel ... AI. • At least three years of experience developing neural network-based algorithms, including ...

As part of our AI team, you'll collaborate closely with engineering teams to deliver high-impact ... Drive performance optimization and scalability of ML systems across edge and cloud environments.

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Edge Ai Machine Learning information

What is an Edge AI Machine Learning?

An Edge AI Machine Learning job involves developing and deploying machine learning models directly on edge devices, such as IoT sensors, mobile devices, and embedded systems. This role requires expertise in optimizing AI models for low-power, low-latency environments while ensuring real-time processing. Professionals in this field work with frameworks like TensorFlow Lite, ONNX, and OpenVINO to implement AI solutions efficiently. They must also handle challenges like model compression, hardware acceleration, and data privacy.

What are some typical challenges faced in an Edge AI Machine Learning role, and how can I prepare for them?

One of the most common challenges in Edge AI Machine Learning is optimizing models to run efficiently on hardware with limited resources, while maintaining acceptable accuracy and speed. You may encounter constraints related to memory, processing power, and connectivity, which require creative engineering and a deep understanding of both machine learning and embedded systems. Collaborating closely with hardware engineers, data scientists, and software developers is typical, as solutions often span multiple technical disciplines. To prepare, staying current with advancements in model compression, quantization, and edge deployment technologies will help you tackle these challenges with confidence.

What are the key skills and qualifications needed to thrive in the Edge AI Machine Learning position?

To thrive as an Edge AI Machine Learning professional, you need a strong background in machine learning algorithms, embedded systems, and proficiency with programming languages such as Python or C++. Familiarity with edge computing platforms (like NVIDIA Jetson, Google Coral), frameworks (TensorFlow Lite, ONNX), and certifications in AI or ML can greatly enhance your qualifications. Strong problem-solving abilities, collaboration, and effective communication skills are important for adapting solutions to diverse environments and working cross-functionally. These abilities enable the successful deployment of efficient and robust AI models directly on devices, meeting the unique challenges of real-time, resource-constrained settings.

How to become an edge AI machine learning engineer?

To become an edge AI machine learning engineer, develop strong skills in machine learning, embedded systems, and programming languages like Python and C++. Gain experience with hardware platforms such as NVIDIA Jetson or Raspberry Pi, and learn to optimize models for low-power, resource-constrained environments. Earning certifications in AI, embedded systems, or IoT can also enhance your qualifications.
What are the most commonly searched types of Edge Ai Machine Learning jobs in Texas? The most popular types of Edge Ai Machine Learning jobs in Texas are:
What cities in Texas are hiring for Edge Ai Machine Learning jobs? Cities in Texas with the most Edge Ai Machine Learning job openings:
Infographic showing various Edge Ai Machine Learning job openings in Texas as of June 2026, with employment types broken down into 5% Internship, 72% Full Time, 6% Part Time, and 17% Contract. Highlights an 95% In-person, and 5% Remote job distribution.

AI and Machine Learning Engineer

Hewlett Packard Enterprise

Spring, TX • Hybrid

Full-time

Posted 3 days ago

New


Hewlett Packard Enterprise rating

8.4

Company rating: 8.4 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

36th of 156 rated electronics manufacturers


Job description

AI and Machine Learning EngineerThis role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world.Our culture thrives onfinding new and better ways to accelerate what's next.We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs.We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you.Open up opportunities with HPE.

Job Description:

High Performance Computing, AI and Labs are a critical element of HPE. We are focused on delivering innovative solutions that accelerate our customers' digital transformation, enabling them to tackle their complex, and data-intensive workloads. Combining deep expertise and the development of the world's most cutting-edge, high-performance supercomputers, is defining the next era of computing delivering valuable insight & innovation. Join us and redefine what's next for you.

Responsibilities:

  • Installs and configures complex IT infrastructure components (servers, storage, network)

  • Develop software scripts and configurations for automating deployment.

  • Study and improve the performance of Large Language Models run on HPE GPU servers

  • Performssystem levelanalysis of server workloads on variousHPE platforms running DL and ML code to include accelerated hardware and high-speed networks like InfiniBand

  • Writes white papers and other guidance documents for AI workload and model selection

  • Captures and reviews system performance data, logs, traces to understand workload behaviour

  • Develops software and scripts that help analyse AI workload performance data

  • Communicates technical work well and can provide summaries of work to non-technical colleagues

  • Works with software and hardware partners in optimizing systems and resolving performance issues

  • Documents and reports issues discovered when testing and evaluating the systems

  • Communicates project status and concerns to management in a timely manner

  • Provides guidance to less-experienced staff members.

  • Runs AI and HPC benchmarks.

Education and Experience Required:

  • Master's degree or PhD in Computer Science, Engineering, Information Technology or Systems, or relevant field.

  • 5+ years of experience.

Knowledge and Skills:

  • 5+ years of experience in Machine Learning/Artificial Intelligence and 5+ years of experience in HPC

  • Experience running NCCL, HPL and AI benchmarks.

  • Experience working with containers and distributed deep learning and neural networks, to include transformers used in generative AI projects

  • Experience working with High Performance Computer Servers, High Performance Networking, and associated software, including resource managers like Slurm

  • Experience working with Weka I/O, NFTS and Lustre File Systems

  • Programming experience in Python, C, C++

  • Strong analytical and critical thinking skills

  • Scripting, process automation and CI/CD are strongly desired

  • Must be a self-starter and be able to work with minimum supervision in a semi-remote setting

Additional Skills:

Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security-First Mindset.

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

#unitedstates

Job:

Engineering

Job Level:

TCP_03"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
- United States of America: Annual Salary USD 120,500 - 276,500 in Texas
The listed salary range reflects base salary. Variable incentives may also be offered."

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

Recruitment Fraud Alert

We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.

All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual's own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.


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