ZipRecruiter

Log In

1

Gpu Computing Jobs in Texas (NOW HIRING)

Nvidia

Senior GPU Compiler Development Engineer

Austin, TX · On-site

$121K - $160K/yr

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 ...

Bot Auto

GPU Engineer

Houston, TX

Develop and optimize parallel computing algorithms and GPU-accelerated components using technologies such as CUDA. * Collaborate with cross-functional teams to design and improve onboard GPU software ...

Bot Auto

GPU Engineer

Houston, TX · On-site

Develop and optimize parallel computing algorithms and GPU-accelerated components using technologies such as CUDA. * Collaborate with cross-functional teams to design and improve onboard GPU software ...

Introl

Data Center Technician

San Antonio, TX · On-site

$30 - $36/hr

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 ...

YO AI Labs

GPU Programmer - Remote

Dallas, TX · Remote

$60 - $85/hr

Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU-focused fields. * Strong understanding of GPU architecture and performan

New

YO AI Labs

GPU Programmer - Remote

Austin, TX · Remote

$60 - $85/hr

Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU-focused fields. * Strong understanding of GPU architecture and performan

New

YO AI Labs

GPU Programmer - Remote

Houston, TX · Remote

$60 - $85/hr

Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU-focused fields. * Strong understanding of GPU architecture and performan

New

Introl

Data Center Technician

San Antonio, TX · On-site

$30 - $36/hr

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 ...

Nvidia

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 ...

Nvidia

GPU Compiler Engineer

Austin, TX

More recently, GPU deep learning ignited modern AI - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the ...

Nvidia

Senior Performance Engineer - DGX Cloud

Austin, TX · On-site

$103K - $142K/yr

Experience with CUDA, GPU computing systems, and GPU performance analysis * Hands-on experience with deep learning frameworks such as PyTorch or JAX/XLA * Deep understanding of system-level ...

next page

Showing results 1-20

All JobsGpu Computing JobsGpu Computing Jobs in Texas

Gpu Computing information

See Texas salary details

$9

$17

$23

How much do gpu computing jobs pay per hour?

As of Aug 23, 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 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.

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 popular job titles related to Gpu Computing jobs in Texas?

For Gpu Computing jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Gpu Computing jobs in Texas look for?

The top searched job categories for Gpu Computing jobs in Texas are:

Gpu Computing jobs near you
Infographic showing various Gpu Computing job openings in Texas as of August 2026, with employment types broken down into 89% Full Time, 9% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $35,418 per year, or $17 per hour.

Sr. GCP Infra Platform Engineer (AI/ML + Terraform)

Nityo Infotech

Austin, TX • On-site

$65/hr

Full-time

Re-posted 22 days ago

Job description

We are hiring for the below role.

Role: Sr. GCP Infra Platform Engineer (AI/ML + Terraform)
Location: Austin, TX 78758 (100% Onsite)

Preference:

  • FTE only (Non H1B) | Max Salary: $105K–$110K

  • Contract to Hire (for H1B candidates) | Max Rate: $65/hr

Job Description:

  • Bachelor’s or higher degree in Computer Science or equivalent

  • 9+ years professional software engineering experience

  • 3+ years specialized experience in AI/ML infrastructure, distributed training, and scaling large ML models

  • Strong experience with Python and frameworks such as PyTorch, TensorFlow, etc.

  • Hands-on experience with Infrastructure as Code (Terraform, CloudFormation, Pulumi, etc.)

  • Knowledge of distributed computing, GPU computing, and GCP environments

  • Ability to work in highly ambiguous and dynamic environments