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Gpu Computing Jobs in Texas (NOW HIRING)

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GPU Computing * CUDA * NVIDIA GPU Platforms * AI/ML infrastructure deployment * Scientific and engineering applications Virtualization & Cloud * VMware vSphere * Kubernetes * OpenShift * Hybrid cloud ...

PTX enables all GPU Computing applications including HPC, Deep Learning and Autonomous Driving. PTX provides a stable programming model and portable instruction set Architecture (ISA) for NVIDIA GPUs ...

The region supports significant GPU computing requirements for defense and commercial applications. About Introl Introl stands apart as a leader in GPU infrastructure deployments, specializing in ...

The region supports significant GPU computing requirements for defense and commercial applications. About Introl Introl stands apart as a leader in GPU infrastructure deployments, specializing in ...

Senior GPU Architect

Austin, TX

$128K - $174K/yr

The NVIDIA GPU Architecture group is looking for world class architects and software developers to ... A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields ...

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Gpu Computing information

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$9

$17

$23

How much do gpu computing jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for gpu computing in Texas is $17.03, according to ZipRecruiter salary data. Most workers in this role earn between $14.09 and $18.37 per hour, depending on experience, location, and employer.

What is GPU computing?

GPU computing refers to the use of a Graphics Processing Unit (GPU) alongside a Central Processing Unit (CPU) to accelerate computational tasks. GPUs are highly efficient at performing parallel operations, making them ideal for complex calculations in fields like machine learning, scientific simulations, and graphics rendering. Unlike traditional CPUs, GPUs can process thousands of threads simultaneously, greatly speeding up tasks that involve large-scale data processing. This makes GPU computing essential in industries requiring high-performance computing solutions.

What are some common challenges faced by GPU Computing professionals when optimizing code for parallel processing?

One of the main challenges in GPU Computing is efficiently restructuring code to leverage the massive parallelism that GPUs offer. Professionals often encounter issues with memory management, synchronization between threads, and minimizing data transfer between CPU and GPU to avoid bottlenecks. Additionally, debugging parallel code can be complex, as errors may not manifest consistently across runs. Collaborating with software engineers, data scientists, and hardware specialists is typical to ensure optimal performance and scalability in real-world applications.

What is the difference between Gpu Computing vs Data Scientist?

AspectGpu ComputingData Scientist
Required CredentialsKnowledge of GPU architectures, programming skills in CUDA or OpenCLDegree in Computer Science, Statistics, or related fields; strong programming skills
Work EnvironmentHigh-performance computing environments, data centers, research labsOffice settings, research institutions, tech companies
Industry UsageMachine learning, scientific simulations, graphics renderingData analysis, predictive modeling, business insights

Gpu Computing focuses on leveraging GPU hardware for high-speed processing tasks, often requiring specialized programming skills. Data Scientists analyze data to extract insights, using various tools and statistical methods. While both roles involve data and computing, Gpu Computing is more hardware and performance-oriented, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as a GPU Computing Specialist, and why are they important?

To thrive as a GPU Computing Specialist, you need expertise in parallel programming, computer architecture, and a strong foundation in mathematics and algorithms, often supported by a degree in computer science, engineering, or related fields. Familiarity with programming languages like C/C++, CUDA, OpenCL, and experience with GPU hardware and high-performance computing systems are essential. Problem-solving abilities, analytical thinking, and strong collaboration skills help you innovate and work effectively on complex computational projects. These skills ensure efficient development, optimization, and deployment of GPU-accelerated solutions crucial for scientific, engineering, and AI applications.
Infographic showing various Gpu Computing job openings in Texas as of July 2026, with employment types broken down into 83% Full Time, 15% Part Time, and 2% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $35,418 per year, or $17 per hour.
High Performance Computing (HPC) Engineer

High Performance Computing (HPC) Engineer

Peak Systems

Dallas, TX • On-site

$72 - $82/hr

Contractor

Posted 5 days ago

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Job description

High Performance Computing (HPC) Engineer

Travel: Up to 50% (Customer Sites, Industry Events, Project Deployments)
Level: Mid-Senior Engineer
Reports To: Services Delivery Manager / Practice Director

There is a need for this role at Childress, TX.

Relocation Stipend - Monthly $1800.00



Position Overview

We are seeking a highly skilled High Performance Computing (HPC) Engineer to design, deploy, optimize, and support enterprise HPC and AI infrastructure solutions for customers across healthcare, research, education, manufacturing, government, and commercial industries.

The ideal candidate will possess strong technical expertise in HPC architecture, Linux administration, clustering technologies, high-speed networking, storage systems, and workload management. This is a high-visibility, customer-facing role requiring exceptional communication skills and the ability to engage with technical decision-makers, architects, and executive stakeholders.

This position involves significant customer interaction and travel to support solution design workshops, installations, migrations, performance tuning, and ongoing technical advisory services.


Key Responsibilities


Solution Design & Architecture

  • Design and architect enterprise HPC solutions utilizing:
    • Dell PowerEdge Servers
    • Dell PowerScale (Isilon)
    • Dell PowerStore
    • Dell ObjectScale/ECS
    • Dell Integrated Rack Solutions
  • Develop scalable compute, storage, and networking architectures for HPC and AI environments.
  • Perform capacity planning, workload analysis, and performance assessments Deployment & Implementation
  • Install, configure, and integrate HPC clusters at customer locations.
  • Deploy and manage Linux-based clustered environments.
  • Configure high-speed interconnects including:
    • InfiniBand
    • Ethernet (100/200/400GbE)
  • Deploy and support shared storage architectures.

Performance Optimization

Conduct benchmarking and performance analysis.

  • Optimize compute, memory, storage, and network utilization.
  • Identify and resolve bottlenecks affecting HPC workloads.
  • Support customer application tuning initiatives.

Customer Engagement

  • Lead technical discussions with customer engineering and IT teams.
  • Deliver architecture reviews and best-practice recommendations.
  • Serve as a trusted technical advisor throughout the project lifecycle.
  • Provide executive-level technical presentations when required.

Operations & Support

  • Troubleshoot complex hardware, software, networking, and storage issues.
  • Participate in escalated support engagements.
  • Create technical documentation, runbooks, and implementation guides.
  • Assist with disaster recovery and business continuity planning.

Collaboration

  • Work closely with internal engineering teams, product specialists, account managers, and technology partners.
  • Support proof-of-concept engagements and technology demonstrations.
  • Mentor junior engineers and share technical best practices.


Required Technical Skills

Operating Systems

  • Red Hat Enterprise Linux (RHEL)
  • Rocky Linux
  • AlmaLinux
  • SUSE Linux Enterprise Server (SLES)

HPC Cluster Technologies

  • Slurm Workload Manager
  • OpenHPC
  • Bright Cluster Manager (preferred)
  • Warewulf
  • xCAT

Storage Technologies

  • Dell PowerScale / Isilon
  • NFS
  • Lustre
  • BeeGFS
  • GPFS / IBM Spectrum Scale
  • Parallel file systems

Networking

  • InfiniBand
  • RoCE
  • High-speed Ethernet (100/200/400GbE)
  • Network performance analysis
  • RDMA technologies

HPC & AI Workloads

  • MPI (OpenMPI, Intel MPI)
  • GPU Computing
  • CUDA
  • NVIDIA GPU Platforms
  • AI/ML infrastructure deployment
  • Scientific and engineering applications

Virtualization & Cloud

  • VMware vSphere
  • Kubernetes
  • OpenShift
  • Hybrid cloud HPC architectures
  • Azure and AWS HPC services (preferred)

Automation & Scripting

  • Python
  • Bash
  • Ansible
  • Terraform (preferred)
  • Git

Monitoring & Management

  • Grafana
  • Prometheus
  • Nagios
  • Dell OpenManage Enterprise
  • Performance monitoring and capacity reporting


Required Qualifications

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
  • 5-10+ years of experience supporting enterprise Linux and infrastructure environments.
  • 3-5+ years of hands-on HPC deployment and administration experience.
  • Strong troubleshooting skills across servers, storage, networking, and operating systems.
  • Experience working directly with enterprise customers in a consulting, professional services, or systems integration environment.
  • Excellent verbal, written, and presentation skills.
  • Ability to manage multiple customer projects simultaneously.


Preferred Qualifications

  • Experience designing, deploying, or supporting Dell HPC infrastructure and enterprise storage solutions.
  • NVIDIA certification or GPU deployment experience.
  • Red Hat Certification (RHCSA/RHCE).
  • Dell Technologies certifications (preferred).
  • Experience supporting AI and machine learning infrastructure.
  • Experience supporting research, life sciences, manufacturing, financial services, or government HPC environments.


Success Factors

The successful candidate will:

  • Be viewed as a trusted technical advisor by strategic customers.
  • Independently lead complex HPC infrastructure deployments.
  • Resolve challenging performance and infrastructure issues.
  • Communicate effectively with both engineering teams and executive stakeholders.
  • Thrive in a fast-paced, customer-facing consulting environment.


Travel Requirement: Up to 50% travel throughout the United States for customer meetings, solution deployments, health checks, and executive briefings.

This role is ideal for a senior infrastructure engineer, Linux architect, or HPC specialist looking to work with enterprise customers while designing and deploying cutting-edge HPC and AI infrastructure utilizing leading technologies, including Dell, NVIDIA, and other industry-leading platforms.

Company Description

For over 30 years, we’ve helped technology professionals build strong, rewarding careers by offering exposure to Fortune 500 clients and top-tier projects. Whether you're looking to expand your experience in data centers, AI infrastructure, field services, project management, or enterprise IT, we can connect you with exciting opportunities that help you build your career, develop new skills, and work on cutting-edge technology deployments.