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Full Time Cuda Jobs (NOW HIRING)

Codvo.ai

$203K/yr

Edge AI Architect - CUDA / C++ / Computer Vision Experience Level: 10+ Years Department: Edge AI ... Employment Type: FULL_TIME

VTG

High-Performance Computing Engineer

Mclean, VA · On-site

Experience with NVidia, Cray, managing clusters, Slurm, Linux, CUDA, high-speed networks as well as an understanding of the customer's A&A process. Education:UNAVAILABLEEmployment Type: FULL_TIME

LufCo

DSP Engineer

Aberdeen, MD · On-site

$150K - $250K/yr

Technical Lead Job Type: Full-time Clearance Requirement: TS/SCI ( US citizenship is a must ... CUDA parallel computing platform and programming model experience (not required) * C/C++/Java ...

LufCo

DSP Engineer

Aberdeen, MD · On-site

Technical Lead Job Type: Full-time Clearance Requirement: TS/SCI ( US citizenship is a must ... CUDA parallel computing platform and programming model experience (not required) * C/C++/Java ...

LufCo

DSP Engineer

Aberdeen, MD · On-site

$150K - $250K/yr

Technical Lead Job Type: Full-time Clearance Requirement: TS/SCI ( US citizenship is a must ... CUDA parallel computing platform and programming model experience (not required) * C/C++/Java ...

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All JobsFull Time Cuda Jobs

Full Time Cuda information

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$111.5K

$206K

How much do full time cuda jobs pay per year?

As of Jun 20, 2026, the average yearly pay for full time cuda in the United States is $200,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $205,000.00 and $205,000.00 per year, depending on experience, location, and employer.

What is the difference between Full Time Cuda vs Full Time Data Scientist?

AspectFull Time CudaFull Time Data Scientist
Required CredentialsCUDA programming certifications, computer science degreeStatistics, data analysis, programming skills, often a master's or PhD
Work EnvironmentTech companies, AI, machine learning, GPU-intensive tasksBusiness, finance, healthcare, research institutions
Employer & Industry UsageTech firms, hardware manufacturers, AI startupsCorporations, research labs, consulting firms

Full Time Cuda roles focus on GPU programming and parallel computing, often requiring specialized certifications and working in tech-heavy environments. Full Time Data Scientist positions involve data analysis, statistical modeling, and machine learning, typically requiring advanced degrees. While both roles involve technical skills, they serve different industry needs and work settings.

More about Full Time Cuda jobs
What cities are hiring for Full Time Cuda jobs? Cities with the most Full Time Cuda job openings:
What are the most commonly searched types of Cuda jobs? The most popular types of Cuda jobs are:
What states have the most Full Time Cuda jobs? States with the most job openings for Full Time Cuda jobs include:
What job categories do people searching Full Time Cuda jobs look for? The top searched job categories for Full Time Cuda jobs are:
Full Time Cuda jobs near you
Infographic showing various Full Time Cuda job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, and 5% Contract. Highlights an 87% Physical, 6% Hybrid, and 7% Remote job distribution, with an average salary of $200,510 per year, or $96.4 per hour.
Senior Software Engineer, CUDA Core Libraries

Senior Software Engineer, CUDA Core Libraries

Nvidia Corporation

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Posted 13 days ago

Job description

NVIDIA's accelerated computing platform is the foundation of modern HPC and AI.At the core of this platform are the CUDA Core Libraries. C++ and Python libraries that enable developers to write fast, reliable, and scalable GPU-accelerated software! We are hiring a full-time Software Engineer to work on the CUDA Core Libraries that power GPU computing for both C++ and Python developers. This includes projects such as CCCL (Thrust, CUB, libcudacxx), cuda-python, and numba-cuda. You will join the team building the foundational libraries, algorithms, and language/runtime infrastructure that make CUDA a speed-of-light experience for developers across deep learning, scientific computing, and data analytics!
What you'll be doing:
  • Develop and implement CUDA Core Libraries in C++ and/or Python, including parallel algorithms and idiomatic language bindings for core CUDA functionality.
  • Compose, optimize, and evolve GPU algorithms and APIs, from high-level interfaces down to low-level performance tuning involving memory, parallelism, and synchronization.
  • Own features end-to-end: develop, implementation, testing, benchmarking, documentation, and long-term maintenance.
  • Improve developer experience across the stack: CI, tests, benchmarks, packaging, examples, and docs.
  • Collaborate with senior CUDA engineers in design reviews, code reviews, and open-source-style workflows.
  • Engage with real users through issues, performance investigations, and API feedback.

What we need to see:
  • BS, MS, or PhD in Computer Science, Computer Engineering, or a related field or equivalent experience.
  • Minimum of 8+ years of related development experience
  • Strong programming skills in C++, Python, or both, with proven interest in systems-level software (performance, memory, concurrency, API design).
  • Solid understanding of modern C++ (templates, generics, standard library) and/or Python library development and packaging.
  • Practical experience with parallel or heterogeneous programming (CUDA, OpenMP, GPU-accelerated Python, or similar).
  • Experience contributing to production software or open-source libraries, including testing, profiling, and code review.
  • Ability to work independently, scope problems, and drive projects to completion.
  • Clear written communication for technical design and documentation.
  • Comfort navigating large, multi-language codebases (C++, Python, CMake, Pixi, CI systems).

Ways to stand out from the crowd:
  • Strong understanding of CPU/GPU architecture and how hardware details affect performance.
  • Hands-on experience with CUDA C++, CUDA Python, PyTorch, JAX, Numba, CuPy, or similar GPU-accelerated stacks.
  • Familiarity with Thrust, CUB, libcudacxx, or other modern C++/GPU libraries.
  • Experience with compiler infrastructure or tooling (LLVM, Clang tooling, MLIR).
  • Demonstrated interest in developer tools, library design, and making other developers faster.

If you care deeply about performance, enjoy working at the C++/Python boundary, and want to shape the core CUDA libraries relied on by thousands of developers, this role is a direct fit.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 5, 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.
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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