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Cuda Programming Jobs in North Carolina (NOW HIRING)

Nvidia

Senior Software Engineer, CUTLASS Kernels

Durham, NC · On-site

$118K - $156K/yr

Experience with CUDA, OpenCL, HIP, SYCL, Mojo, Pallas, Triton, Mosaic, Halide, or any general-purpose or domain-specific programming language targeting highly parallel accelerators. * Deep ...

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:

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Cuda Programming information

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$25

$49

$74

How much do cuda programming jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for cuda programming in North Carolina is $49.40, according to ZipRecruiter salary data. Most workers in this role earn between $40.00 and $57.69 per hour, depending on experience, location, and employer.

What is the difference between Cuda Programming vs GPU Developer?

AspectCuda ProgrammingGPU Developer
Required CredentialsKnowledge of CUDA, C/C++, parallel computingKnowledge of GPU architecture, CUDA, OpenCL, C/C++
Work EnvironmentHigh-performance computing, scientific research, AIGraphics, gaming, scientific visualization, AI
Industry UsageTech companies, research labs, AI firmsGaming, entertainment, tech, research

While Cuda Programming focuses specifically on writing code using NVIDIA's CUDA platform for parallel processing, GPU Developers have a broader role that includes designing, optimizing, and implementing GPU-based solutions across various platforms and technologies. Both roles require knowledge of GPU architecture and programming languages like C/C++, but GPU Developers often work on a wider range of applications beyond CUDA-specific projects.

Are CUDA programmers in demand?

CUDA programmers are in high demand due to the growing need for high-performance computing in fields like artificial intelligence, scientific research, and data processing. Skills in parallel programming, GPU architecture, and CUDA toolkit are highly valued, and job opportunities are expected to grow as industries adopt GPU acceleration for complex tasks.

What does a CUDA programming developer do?

A CUDA programming developer writes software that leverages NVIDIA's CUDA platform to perform parallel processing on GPUs, optimizing computational tasks such as scientific simulations, machine learning, and image processing. They typically work with C++ and CUDA-specific libraries, debugging and optimizing code for high performance in environments that require intensive data processing.

What are popular job titles related to Cuda Programming jobs in North Carolina?

For Cuda Programming jobs in North Carolina, the most frequently searched job titles are:

What job categories do people searching Cuda Programming jobs in North Carolina look for?

The top searched job categories for Cuda Programming jobs in North Carolina are:

Cuda Programming jobs near you
Infographic showing various Cuda Programming job openings in North Carolina as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 76% In-person, and 24% Remote job distribution, with an average salary of $102,750 per year, or $49.4 per hour.

Senior Software Architect - Deep Learning and HPC Communications

NVIDIA AI

Durham, NC • On-site

$125K - $170K/yr

Full-time

Re-posted 27 days ago

Job description

Job Summary:
NVIDIA AI is at the forefront of innovations in Artificial Intelligence and High Performance Computing. They are seeking a Senior Software Architect to design and implement new communication technologies that enhance AI and HPC workloads, while also investigating performance improvements in communication systems.
Responsibilities:
• Investigate opportunities to improve communication performance by identifying bottlenecks in today's systems.
• Design and implement new communication technologies to accelerate AI and HPC workloads.
• Explore innovative solutions in HW and SW for our next generation platforms as part of co-design efforts involving GPU, Networking, and SW architects.
• Build proofs-of-concept, conduct experiments, and perform quantitive modeling to evaluate and drive new innovations.
• Use simulation to explore performance of large GPU clusters (think scales of 100s of 1000s of GPUs)
Qualifications:
Required:
• M.S./Ph.D. degree in CS/CE or equivalent experience.
• 5+ years of relevant experience.
• Excellent C/C++ programming and debugging skills.
• Experience with parallel programming models (MPI, SHMEM) and at least one communication runtime (MPI, NCCL, NVSHMEM, OpenSHMEM, UCX, UCC).
• Deep understanding of operating systems, computer and system architecture.
• Solid in fundamentals of network architecture, topology, algorithms, and communication scaling relevant to AI and HPC workloads.
• Strong experience with Linux.
• Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.
Preferred:
• Expertise in related technology and passion for what you do.
• Experience with CUDA programming and NVIDIA GPUs.
• Knowledge of high-performance networks like InfiniBand, RoCE, NVLink, etc.
• Experience with Deep Learning Frameworks such PyTorch, TensorFlow, etc.
• Knowledge of deep learning parallelisms and mapping to the communication subsystem.
• Experience with HPC applications.
• Strong collaborative and interpersonal skills and a proven track record of effectively guiding and influencing within a dynamic and multi-functional environment.
Company:
Explore the latest breakthroughs made possible with AI. Founded in , the company is headquartered in Santa Clara, CA, US, , with a team of 10001+ employees. The company is currently Late Stage.

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