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Gpu Computing Jobs (NOW HIRING)

VTG

High-Performance Computing Engineer

Mclean, VA · On-site

The ideal candidate will bring deep technical expertise in large-scale HPC environments, cluster management, GPU computing, and high-speed networking. Do you have what it takes? * Active Top Secret ...

VTG

High-Performance Computing Engineer

Mclean, VA

The ideal candidate will bring deep technical expertise in large-scale HPC environments, cluster management, GPU computing, and high-speed networking. Do you have what it takes? * Active Top Secret ...

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How much do gpu computing jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for gpu computing in the United States is $18.28, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $19.71 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.
More about Gpu Computing jobs
What states have the most Gpu Computing jobs? States with the most job openings for Gpu Computing jobs include:
What job categories do people searching Gpu Computing jobs look for? The top searched job categories for Gpu Computing jobs are:
Gpu Computing jobs near you
High-Performance Computing Engineer

High-Performance Computing Engineer

VTG

Mclean, VA • On-site

Full-time

Posted 21 days ago

Job description

Overview
iota IT, a subsidiary of VTG, is seeking a High-Performance Computing Engineer in McLean, VA.
What will you do?
  • The highly skilled High Performance Computing Engineer to design, implement, and maintain advanced computing solutions in support of mission-critical operations.
  • The ideal candidate will bring deep technical expertise in large-scale HPC environments, cluster management, GPU computing, and high-speed networking.

Do you have what it takes?
  • Active Top Secret/Sensitive Compartmented Information (TS/SCI) clearance, with polygraph.
  • Bachelor's Degree in Computer Science, Engineering or related field.
  • Experience with NVidia, Cray, managing clusters, Slurm, Linux, CUDA, high-speed networks as well as an understanding of the customer's A&A process.

Apply