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Gpu Jobs in Raleigh, NC (NOW HIRING)

Nvidia

Senior GPU Memory Architect

Durham, NC

This GPU memory architecture team creates new, innovative products tailored to NVIDIA's world-changing solutions for autonomous vehicles, AI, gaming, mobile systems. What you will be doing:

Nvidia

Senior GPU Architect

Durham, NC

$125.10K - $170.10K/yr

The NVIDIA GPU Architecture group is looking for world class architects and software developers to join and lead our various architecture efforts. A key part of NVIDIA's strength is to innovate in ...

Nvidia

Senior GPU Memory Architect

Durham, NC

Develop architecture and micro-architecture features to improve the state-of-the-art in GPU memory systems, optimizing along the axes of perf/W, perf/mm, and perf/$. * Develop and enhance ...

Nvidia

Senior GPU Memory Architect

Durham, NC

Develop architecture and micro-architecture features to improve the state-of-the-art in GPU memory systems, optimizing along the axes of perf/W, perf/mm, and perf/$. * Develop and enhance ...

MCNC

AI Infrastructure Engineer Intern

Durham, NC · On-site

Job Summary The AI Infrastructure Engineer Intern will support MCNC AI infrastructure initiatives involving GPU systems, cloud environments, and advanced computing platforms used for artificial ...

Artech

AI Infra engineer

Morrisville, NC · On-site

$100.60K - $131.90K/yr

Monitor and maintain GPU servers/workstations, including diagnosing and resolving hardware failures (e.g., GPU faults, power issues, cooling problems). Coordinate repairs, replacements, or upgrades ...

Deloitte

HPC AI Solution Architect (S2S)

Raleigh, NC · On-site

$61.25 - $80.75/hr

The role involves designing and deploying integrated architectures for GPU-accelerated AI factories and high-performance computing infrastructure, collaborating closely with AI specialists and ...

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How much do gpu jobs pay per hour?

As of May 28, 2026, the average hourly pay for gpu in Raleigh, NC is $53.41, according to ZipRecruiter salary data. Most workers in this role earn between $52.60 and $63.08 per hour, depending on experience, location, and employer.

What is a GPU job?

A GPU job refers to a computing task that utilizes a Graphics Processing Unit (GPU) for acceleration. GPUs are specialized processors designed for parallel processing, making them ideal for tasks like machine learning, scientific simulations, and rendering. Many software applications offload intensive computations to GPUs to improve performance and efficiency. Jobs related to GPUs can involve programming, optimization, and hardware configuration in fields like AI, gaming, and data analysis.

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

To thrive as a GPU Engineer, you need a solid background in computer engineering, mathematics, and programming languages such as C++ or CUDA, often supported by a relevant degree. Familiarity with GPU architectures, parallel computing frameworks, and tools like OpenCL or Vulkan is typically required. Analytical thinking, problem-solving, and teamwork are essential soft skills for innovating and debugging complex systems. These abilities are crucial for optimizing performance, ensuring compatibility, and driving advancements in graphics and computational workloads.

What are some common challenges faced by GPU engineers when optimizing performance for various applications?

GPU engineers often encounter challenges such as balancing high computational throughput with power efficiency, ensuring compatibility across different hardware architectures, and optimizing code for parallel processing. They must also troubleshoot bottlenecks in memory bandwidth and latency that can impact performance. Collaboration with software developers and hardware architects is crucial to identify and resolve these issues, and staying updated with the latest advances in GPU technologies is essential for continued success.

What is a GPU?

A GPU, or Graphics Processing Unit, is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images and graphics for display. While originally developed for rendering graphics in video games and visual applications, GPUs are now widely used for parallel processing tasks in areas such as artificial intelligence, data science, and scientific computing. Their architecture allows them to handle thousands of operations simultaneously, making them much faster than traditional CPUs for certain workloads.

What is the difference between Gpu vs Data Scientist?

AspectGpuData Scientist
Required CredentialsKnowledge of parallel computing, programming skills (CUDA, OpenCL)Degree in Computer Science, Statistics, or related fields; programming skills
Work EnvironmentHardware-focused, technical, often in R&D or engineering teamsData analysis, modeling, research in various industries
Industry UsageTech, gaming, AI, machine learningFinance, healthcare, tech, marketing

Gpu specialists focus on hardware and parallel processing for computing tasks, while data scientists analyze data to extract insights. Both roles require technical skills, but Gpu roles are more hardware-oriented, whereas data scientists focus on data analysis and modeling.

More about Gpu jobs
What are the most commonly searched types of Gpu jobs in Raleigh, NC? The most popular types of Gpu jobs in Raleigh, NC are:
What are popular job titles related to Gpu jobs in Raleigh, NC? For Gpu jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Gpu jobs in Raleigh, NC look for? The top searched job categories for Gpu jobs in Raleigh, NC are:
Gpu jobs near you
Infographic showing various Gpu job openings in Raleigh, NC as of May 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $111,090 per year, or $53.4 per hour.
Senior GPU Memory Architect

Senior GPU Memory Architect

Nvidia

Durham, NC

Full-time

Posted 29 days ago

Job description

We are now looking for a Senior GPU Memory Architect.

NVIDIA is seeking a motivated architect to work with a team in solving complex problems while optimizing performance, area, complexity, and power on leading-edge silicon processes. This GPU memory architecture team creates new, innovative products tailored to NVIDIA's world-changing solutions for autonomous vehicles, AI, gaming, mobile systems.

What you will be doing:

  • Developing architecture and micro-architecture to improve the state-of-the-art in GPU memory system and memory management optimizing along the axes of performance, power efficiency, complexity, area, effort, and schedule.

  • Participating in performance simulation of features to improve memory access efficiency.

  • Implementing and maintaining high-level functional and performance models.

  • Analyzing benchmarks, application workloads and performance simulation results to identify areas for microarchitecture optimizations.

  • Defining and performing experiments to study the machine in action, presenting experiment results to the larger group and proposing mechanisms for improvement.

  • Creating architectural specifications and customer-facing documents. Working with partners in the industry to generate specifications which take into account software interfaces to the GPU.

  • Debugging performance and functional issues with high-level models, RTL simulation, and silicon.

What we need to see:

  • Master degree or equivalent experience in Electrical Engineering, Computer Science, Computer Engineering or related field. A PhD with a focus in computer architecture is a plus.

  • 6+ years of meaningful work experience in GPU or CPU Architecture and development specifically in the area of memory caching and interconnects.

  • Strong communication and interpersonal skills are required along with the ability to work in a dynamic, product oriented, distributed team. Your history of successfully mentoring junior engineers and interns is a huge plus.

Ways to stand out from the crowd:

  • Experience with hardware memory management unit, prefetching, or memory subsystems.

  • Practical experience with multi-core systems and memory coherency.

Do you desire to be a part of a team of talented engineers developing ground-breaking GPU architectures from specification through implementation to extend the state of the art in GPU performance and functionality? Are you motivated to solve complex problems while optimizing performance, area, complexity, and power? If so, our GPU memory architecture group is looking for you. With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented market opportunities, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for computer architecture and technology, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 26, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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