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

Nvidia

Senior ASIC Design Engineer - GPU

Durham, NC · Hybrid

... for a GPU using advanced verification methodologies. * Contribute to architecture decisions ... Collaborate with architects, designers, and software engineers across sites to accomplish your ...

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

... 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 Software Engineer, CUTLASS Platform

Durham, NC · On-site

$118K - $156K/yr

Collaborate with GPU architecture, CUDA, and NVVM/PTX compiler teams to provide feedback on programming models and to assess the performance of future GPU hardware features. What we need to see:

Nvidia

Principal Graphics Developer Tools Engineer

Durham, NC · On-site

$135K - $167K/yr

Design and prototype new tools that can evolve into production-ready software. * Collaborate with GPU architects, driver engineers, SDK teams, and graphics developers to understand future needs and ...

Nvidia

Senior GPU Architect

Durham, NC · On-site

$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 ...

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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 28, 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
Senior Software Engineer - GPU Local AI Platforms

Senior Software Engineer - GPU Local AI Platforms

Nvidia

Durham, NC

$118K - $156K/yr

Full-time

Posted 3 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 245 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's Local AI team is building the software stack that makes large language models and generative AI applications run at maximum efficiency on NVIDIA edge AI hardware. The AI ecosystem moves fast; our job is to make sure end users get the best experience. We own the platform - performance, CI/CD pipelines, validated recipes, and model bring-up infrastructure - that lets developers run groundbreaking LLMs out of the box. The open-source community builds fast; our platform is what turns community innovation into something developers and partners can rely on at scale.

What you'll be doing:

  • Track and evaluate innovations in leading open-source LLM inference frameworks - identify performance-critical features and algorithmic improvements relevant to NVIDIA edge AI hardware

  • Analyze how new model architectures and inference algorithms (attention variants, MoE routing, speculative decoding, multi-token prediction, quantized inference) map onto NVIDIA GPU architecture - identify mismatch, fallback paths, and optimization opportunities

  • Characterize multi-node inference behavior: collective communication primitives (NCCL/RCCL), topology-aware all-reduce strategies, and parallelism efficiency on edge cluster configurations

  • Produce performance analysis reports mapping theoretical hardware limits (memory bandwidth, FLOP/s, interconnect throughput) to observed inference throughput, latency, and utilization

  • Own the model validation workflow for new model releases: architecture compatibility assessment, inference recipe development, performance characterization, and publication to developer recipe sites

  • Develop and maintain developer-facing inference recipes: keep them accurate as frameworks evolve, automate staleness detection, and build feedback loops from CI results to recipe updates

  • Engage with community and partners on model bring-up questions; serve as the technical point of contact for hardware-specific inference issues related to partner concerns

What we need to see:

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

  • 12+ years of software engineering with depth in GPU computing, ML systems, or high-performance inference

  • Strong Python or C++ programming, software design, and software engineering skills.

  • Hands-on experience with GPU kernel development or optimization (CUDA/C++, Triton, or equivalent) - you understand how thread blocks, memory hierarchy, and warp execution affect real-world performance

  • Working knowledge of LLM inference internals: attention mechanisms, KV-cache management, continuous batching, quantization formats, and tensor parallelism

  • Container engineering expertise: multi-architecture Docker or OCI builds, layer optimization, runtime configuration, NVIDIA Container Toolkit

  • Strong analytical skills: ability to form a performance hypothesis, design an experiment, interpret results, and communicate findings clearly

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 28, 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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