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Gpu Jobs in Raleigh, NC (NOW HIRING)

Nvidia

EDA Workflow Optimization Engineer

Durham, NC · Hybrid

$107K - $127K/yr

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 ...

Lenovo

Director, Technical Project Manager

Morrisville, NC · On-site

$190 - $210/hr

If you bring deep technical expertise in server, storage, or GPU program management, master the art of customer engagement, and thrive in a dynamic global environment, we want to hear from you. Own ...

Nvidia

Senior ASIC Timing Engineer

Durham, NC · Hybrid

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 ...

Nvidia

Senior ASIC Verification Engineer

Durham, NC · Hybrid

NVIDIA is seeking an outstanding Senior ASIC Verification Engineer to verify the design and implementation of the world's leading SoC's and GPU's. This position offers the opportunity to have a real ...

Vadum Inc

Electronic Warfare Systems Architect

Raleigh, NC · On-site

$217K/yr

  • Medical

  • Retirement

Hardware/Software Integration - Align algorithm development with hardware constraints (FPGA, GPU, CPU, embedded systems). - Define digital signal processing requirements and data flows across system ...

Teledyne FLIR LLC

Software Engineer

Durham, NC · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Knowledge of computer architecture (GPU/FPGA/distributed computing), operating systems, networking, storage systems, Unix/Linux, MATLAB, etc. is a plus * Excellent interpersonal and communication ...

Vadum Inc

Electronic Warfare Systems Architect

Raleigh, NC

$217K/yr

  • Medical

  • Retirement

Hardware/Software Integration - Align algorithm development with hardware constraints (FPGA, GPU, CPU, embedded systems). - Define digital signal processing requirements and data flows across system ...

Teledyne FLIR LLC

Research Scientist

Durham, NC · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Design and implement advanced algorithms on PC, GPU, and embedded architectures * Perform sophisticated signal processing, statistical analysis, and systems engineering tasks * Support hardware ...

Teledyne

Research Scientist

Durham, NC

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Design and implement advanced algorithms on PC, GPU, and embedded architectures * Perform sophisticated signal processing, statistical analysis, and systems engineering tasks * Support hardware ...

Vadum, Inc.

Electronic Warfare Systems Architect

Raleigh, NC · On-site

$125K - $180K/yr

  • Medical

  • Retirement

Hardware/Software Integration - Align algorithm development with hardware constraints (FPGA, GPU, CPU, embedded systems). - Define digital signal processing requirements and data flows across system ...

Teledyne

Software Engineer

Durham, NC

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Knowledge of computer architecture (GPU/FPGA/distributed computing), operating systems, networking, storage systems, Unix/Linux, MATLAB, etc. is a plus * Excellent interpersonal and communication ...

Nvidia

Senior VLSI CAD Software Engineer

Durham, NC · On-site

$118K - $156K/yr

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 ...

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Gpu information

See Raleigh, NC salary details

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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.

EDA Workflow Optimization Engineer

Nvidia

Durham, NC • Hybrid

$107K - $127K/yr

Full-time

Re-posted 25 days 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 reinvented itself over two decades, inventing the GPU in 1999 to reshape PC gaming and modern computer graphics. As an engineer in our EDA Workflow Optimization team, you will partner closely with our engineering teams worldwide. You will understand workflows covering the full chip design process from inception through study, architecture, design, verification, emulation, layout, packaging, power-on and production. You will then guide teams to improve, and sometimes re-invent those flows. You will enable our engineers to have the best tools on the planet to make the most innovative chips in the world. You will perform investigations to understand flaws and opportunities, construct metrics to continuously measure performance of our flows and services, and other infrastructure. You will work with your team of EDA and software experts to build new infrastructure in an agile, production software environment. You will continuously innovate and enhance scalable, reliable, high performance systems and tools to enable the next generation of chips!

What you'll be doing:

  • Work in a diverse team performing fast paced investigations to empower our engineers to develop at the speed of light.

  • Participate in the full life-cycle of tool development, test, and deployment.

  • Work closely with other team members and chip engineers to understand and optimize how workflows use the compute and storage environments.

  • Build metrics that are reliable and easy to use by hundreds of engineers around the world.

  • Continuously improve our chip development process.

  • Directly contribute to the overall quality and time to market for our next generation chips.

What we need to see:

  • Strong experience investigating and debugging complex, multi-discipline problems in a UNIX engineering environment.

  • Hands-on experience with architectural decisions in technologies (storage, networking, compute) our chip engineers depend on.

  • Experience with ASIC, VLSI, CAD/EDA or mixed signal design workflow environments.

  • Hands-on experience with EDA tools.

  • Experienced in UNIX Systems programming and automation using Python and/or Shell.

  • Authoritative level usage of UNIX and UNIX utilities.

  • Excellent planning and communication skills.

  • Experience in applying data analysis principles and influencing data-driven decisions.

  • Flexibility/adaptability working in a dynamic environment with changing requirements.

  • BS in Computer Science or equivalent experience; MS (preferred).

  • 5+yrs of relevant experience.

Ways to stand out from the crowd:

  • Experience with job schedulers (in particular IBM Spectrum LSF and/or SLURM).

  • Hands-on experience running GPU-based workloads in a batch computing environment and a deep understanding of distributed system principles.

  • Strong programming and debugging skills with C/C++, Python, and Perl on UNIX.

  • A passion for improving engineering productivity and efficiency via data-driven philosophy.

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 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.

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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