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Internship Gpu Programming Jobs in Raleigh, NC (NOW HIRING)

This GPU memory architecture team creates new, innovative products tailored to NVIDIA's world ... Your history of successfully mentoring junior engineers and interns is a huge plus. Ways to stand ...

Internship Gpu Programming information

See Raleigh, NC salary details

$13

$24

$37

How much do internship gpu programming jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for internship gpu programming in Raleigh, NC is $24.71, according to ZipRecruiter salary data. Most workers in this role earn between $20.10 and $28.03 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship GPU Programming, and why are they important?

To thrive as an Internship GPU Programming, you need a solid background in computer science, mathematics, and programming languages such as C++ and Python, often supported by coursework or personal projects in parallel computing. Familiarity with GPU programming frameworks like CUDA or OpenCL and version control systems (e.g., Git) is typically expected. Strong analytical thinking, attention to detail, and effective communication help interns collaborate with teams and troubleshoot complex issues. These skills and qualities are essential for efficiently developing, optimizing, and debugging GPU-accelerated applications in a fast-paced, technical environment.

What types of projects or tasks can an intern expect to work on in a GPU programming internship?

As a GPU programming intern, you can expect to work on tasks such as optimizing existing code for GPU acceleration, developing parallel algorithms using CUDA or OpenCL, and assisting in the profiling and debugging of GPU applications. Interns often collaborate with researchers and software engineers to implement new features or improve the performance of computational workflows. You may also contribute to documentation and testing, gaining exposure to real-world applications in fields like machine learning, scientific computing, or graphics rendering.

What is an Internship in GPU Programming?

An Internship in GPU Programming is a temporary position, often held by students or recent graduates, where individuals gain hands-on experience working with Graphics Processing Units (GPUs) to develop, optimize, and accelerate software applications. Interns typically work on projects involving parallel computing, machine learning, graphics rendering, or scientific simulations using programming languages such as CUDA or OpenCL. These internships provide an opportunity to learn from experienced engineers, contribute to real-world projects, and develop specialized skills that are valuable in technology and research industries.
Infographic showing various Internship Gpu Programming job openings in Raleigh, NC as of June 2026, with employment types broken down into 83% Full Time, 14% Part Time, and 3% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $51,391 per year, or $24.7 per hour.
Senior GPU Memory Architect

Senior GPU Memory Architect

Nvidia

Durham, NC

Full-time

Posted 28 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