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Gpu Jobs in Raleigh, NC (NOW HIRING)

Nvidia

Senior ASIC Power Engineer

Durham, NC · On-site

Develop innovative HW, GPU and system designs to extend the state of the art performance and efficiency * You are expected to understand the design and implementation, develop power metrics and drive ...

Nvidia

Senior System Simulation Architect

Durham, NC

Develop full-system functional models capable of running complex multi-threaded heterogeneous (CPU/GPU) workloads - with special focus on the CPU subsystem. * Integrate functional models from various ...

Nvidia

Senior Developer Technology Engineer - AI

Durham, NC · Hybrid

$52.75 - $69.50/hr

In this position, you will research and develop techniques to GPU accelerate workloads in deep learning, machine learning or other AI domains. * Work directly with other technical experts in their ...

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Gpu information

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How much do gpu jobs pay per hour?

As of Aug 16, 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?

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 a GPU engineer?

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?

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 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.

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 August 2026, with employment types broken down into 90% Full Time, 6% Part Time, 1% Temporary, and 3% Contract. Highlights an 81% Physical, 7% Hybrid, and 12% Remote job distribution, with an average salary of $111,090 per year, or $53.4 per hour.

Senior Machine Learning Graphics Engineer, AI for Experiences

Nvidia

Durham, NC

$135K - $167K/yr

Full-time

Re-posted 20 hours ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies

Job description

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

NVIDIA is searching for a world-class engineer in graphics and AI to join our neural graphics product team. If you agree with us that the most exciting thing about the AI revolution is applying it to solve real problems, this team will be an excellent fit for you! We are passionate about applications in generative AI, gaming, augmented reality, user-generated content, computer vision, and other areas, with the goal of improving visual fidelity, gameplay, or other domains within the gaming and pro-visualization markets. Working with other teams throughout the company, you will productize promising research, as well as develop new features through your own work.

What you'll be doing:

  • Use AI for solving product problems in gaming and other interactive experiences.

  • Build upon the latest research to create new models and invent new ways of applying AI to advance neural graphics and gaming.

  • Create prototypes to demonstrate real-life applications of your ideas and to accelerate productization.

  • Keep up with the latest AI/DL research and collaborate with diverse teams (both internal and external to NVIDIA), including AI/DL researchers, hardware architects, and software engineers.

  • Participate in technology transfers to and from teams across NVIDIA.

What we need to see:

  • Master's in computer science/engineering, Machine Learning, AI, and related fields (or equivalent experience)

  • 12+ years of machine learning / deep learning research or work experience

  • Knowledge of application areas such as real-time computer graphics, CV, and game development.

  • Expertise with programming systems such as Python, C+, CUDA, and deep learning frameworks such as TensorFlow and PyTorch. Very strong programming skills.

  • A proven track record of delivering complex products and technologies spanning multiple teams and functional areas.

Intelligent machines powered by AI computers that can learn, reason, and interact with people are no longer science fiction. Image recognition and speech recognition - GPU deep learning has provided the foundation for machines to learn, perceive, reason, and solve problems. The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for deep learning, and NVIDIA is known as "the AI computing company."

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 20, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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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