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Software Engineer Gpu Jobs in Raleigh, NC (NOW HIRING)

Teledyne FLIR LLC

Software Engineer

Durham, NC · On-site

... Software Engineer to support advanced research and development projects that require algorithm and ... Knowledge of computer architecture (GPU/FPGA/distributed computing), operating systems, networking ...

Teledyne

Software Engineer

Durham, NC · On-site

... Software Engineer to support advanced research and development projects that require algorithm and ... Knowledge of computer architecture (GPU/FPGA/distributed computing), operating systems, networking ...

Nvidia

Senior GPU Architect

Durham, NC

$125K - $170K/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 VLSI CAD Software Engineer

Durham, NC

$118K - $156K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... NVIDIA is seeking a talented Software Engineer to join our small team building custom, high-impact ...

SAS

DevOps Engineer

Cary, NC · On-site

$49.25 - $67.50/hr

About the job The Applied AI & Modeling (AAIM) Division seeks a Software Engineer skilled in GPU infrastructure, deployment, and administration to maintain scalable, secure cloud environments for ...

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Software Engineer Gpu information

See Raleigh, NC salary details

$61.7K

$143.4K

$199.8K

How much do software engineer gpu jobs pay per year?

As of Jul 7, 2026, the average yearly pay for software engineer gpu in Raleigh, NC is $143,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,600.00 and $168,200.00 per year, depending on experience, location, and employer.

What is the difference between Software Engineer Gpu vs Software Engineer?

AspectSoftware Engineer GpuSoftware Engineer
Required SkillsGPU programming, parallel computing, CUDA/OpenCLGeneral software development, algorithms, coding
Work EnvironmentHigh-performance computing, graphics, AIWeb, mobile, enterprise applications
CertificationsCUDA certifications, relevant degreesVaries widely, often general CS degrees
Industry UsageGraphics, AI, scientific computingSoftware development across industries

Software Engineer Gpu specializes in GPU-based programming for high-performance tasks, while a Software Engineer has a broader focus on general software development. Both roles require strong coding skills, but GPU engineers focus more on parallel processing and graphics technologies. The choice depends on your interest in graphics and high-performance computing versus general software development.

How does a Software Engineer specializing in GPU typically collaborate with hardware and other engineering teams?

As a Software Engineer focusing on GPU, you will frequently work closely with hardware engineers, driver developers, and performance analysts. Collaboration often involves optimizing software to leverage GPU capabilities, troubleshooting performance bottlenecks, and ensuring compatibility with evolving hardware architectures. Effective communication and cross-functional teamwork are essential, as solutions often require aligning software design with hardware constraints and roadmaps. This collaborative environment not only broadens your technical understanding but also provides opportunities to learn from diverse engineering disciplines.

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

To thrive as a Software Engineer GPU, you need strong programming skills in C/C++, parallel computing concepts, and a solid background in computer science or related fields. Familiarity with GPU programming frameworks such as CUDA or OpenCL, version control systems, and performance profiling tools is typically required. Analytical thinking, problem-solving abilities, and effective teamwork are essential soft skills for excelling in this role. These competencies ensure the development of optimized, high-performance software that leverages GPU architectures for demanding computational tasks.

What are Software Engineer GPU roles?

A Software Engineer GPU is a specialist who designs, develops, and optimizes software that runs on Graphics Processing Units (GPUs). These engineers focus on maximizing the performance of applications—such as graphics rendering, machine learning, or scientific computation—by leveraging the parallel processing power of GPUs. They often work with languages like CUDA or OpenCL and collaborate with hardware teams to ensure efficient integration of software and GPU hardware. Their work is vital in industries like gaming, AI, automotive, and high-performance computing.
What are the most commonly searched types of Software Engineer Gpu jobs in Raleigh, NC? The most popular types of Software Engineer Gpu jobs in Raleigh, NC are:
Software Engineer Gpu jobs near you
System Software Engineer - Data Center GPU Compute Diagnostics

System Software Engineer - Data Center GPU Compute Diagnostics

Nvidia

Durham, NC

$167K - $198K/yr

Full-time

Posted 17 days ago

Job description

We are seeking a system software engineer to work on next-generation Data Center GPU diagnostics for rack-scale AI supercomputer systems. Our charter is to build applications and compute workloads that test and heavily stress GPU compute engines, HBM memory, cache hierarchy, PCIe/NVLinkinterfaces, power delivery, and thermal behavior, and to use those applications in silicon/system bring-up along with packaging such tools for manufacturing and customer use. In this role you will partner with a senior engineer leading the team's CUDA kernel and GEMM diagnostics work, owning well-scoped pieces of the codebase end-to-end while ramping on GPU microarchitecture and silicon characterization. The best candidates will have experience writing low-level diagnostic, performance, or stress software for complex hardware systems, ideally including experience with GPUs, CUDA kernels, GEMM-style workloads, CPUs,NICsor high-speed interconnects such as PCIe.

Good interpersonal skills arerequiredas this role will involve close collaboration with hardware architecture, silicon validation,manufacturingand field teams. In addition, the engineer will grow their knowledge of operating systems, computer architecture, GPU memory, voltage/frequency behavior, thermal limits, high-speed buses, and modern AI development and analysis tools to efficientlyvalidateand test next-generation processors and systems.Join an exciting,rewardingandfast pacedenvironment!

Whatyou'llbe doing:

  • Working closely with hardware architecture, driver, manufacturing, and field teams through the product development lifecycle of rack-scale AI systems.

  • Implementing andmaintainingCUDA/C++ diagnostic workloads and software infrastructure used in chip development, validation, productization, and field triage.

  • Writing and tuning GPU compute tests that stress Tensor Cores, SMs, L2/cache hierarchy, HBM memory, and related power/thermal operating points.

  • Implementing and tuning GEMM-style diagnostic workloads, including tests combined withadditionalloadinNVLink,PCIe or CPU subsystems.

  • Contributing to higher-level AI workload tests, includingPyTorch-based large model workloads that stress GPUs, memory, interconnects, thermals, and system software under realistic rack-scale AI use cases.

  • Bringing up andvalidatingnew hardware features with pre-beta GPU drivers, low-level diagnostic software, and system telemetry, under guidance from the technical lead.

  • Triaging and debugging failures involving ECC, HBM behavior, thermal limits, voltage/frequency margining, and PCIe/NVLinkerrors.

What we need to see:

  • BS or MS degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.

  • 5+ years of system software, GPU software, embedded software, or hardware validation experience.

  • Experience writing low-level diagnostics, interacting with device firmware and hardware level debuggers.

  • Strong C/C++ and Python programming skills.

  • Exposure to GPU architecture, CUDA kernels, GPU compute workloads, or related accelerator programming is strongly preferred.

  • Working knowledge of memory systems, ECCbehaviorandDMAengines.

  • Familiarity with GEMM-styleworkloads.

  • Awareness of voltage/frequency characterization, thermal testing, power stress, or related silicon validation concepts such asVmin/Fmax and P-state testing.

  • Experience using modern AI development and analysis tools to improve engineering velocity, including code development, debugging, and test creation.

  • Strong problem solving and low-level debugging skills.

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.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 24, 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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