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Cuda Software Engineer Jobs (NOW HIRING)

Nvidia

System Software Engineer - CUDA Chips

Santa Clara, CA · On-site

$203K - $240K/yr

... CUDA driver interaction with GPU hardware, kernel mode drivers, and the operating system. This role incorporates strong system software programming skills, a detailed understanding of operating ...

Nvidia

System Software Engineer - CUDA Chips

Santa Clara, CA · On-site

$203K - $240K/yr

... CUDA driver interaction with GPU hardware, kernel mode drivers, and the operating system. This role incorporates strong system software programming skills, a detailed understanding of operating ...

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Cuda Software Engineer information

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$63.5K

$147.5K

$205.5K

How much do cuda software engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for cuda software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What is a CUDA software engineer?

CUDA Software Engineers are specialists who develop software using NVIDIA's CUDA (Compute Unified Device Architecture) platform to leverage the parallel processing power of GPUs. They optimize algorithms and applications for high performance on CUDA-enabled devices, often in fields like scientific computing, machine learning, and graphics. Their work involves writing and debugging code in languages such as C, C++, or Python with CUDA extensions, and collaborating with teams to ensure efficient execution of compute-intensive tasks.

What are the key skills and qualifications needed to thrive as a CUDA software engineer?

To thrive as a CUDA Software Engineer, you need strong proficiency in C/C++ programming, parallel computing concepts, and a solid understanding of GPU architectures, typically supported by a computer science or related degree. Familiarity with NVIDIA CUDA Toolkit, GPU debugging/profiling tools, and experience with performance optimization are essential. Analytical thinking, problem-solving, and effective teamwork skills help you tackle complex computational challenges and collaborate on large-scale projects. These skills are crucial to efficiently develop high-performance GPU-accelerated applications and deliver optimized solutions in demanding technical environments.

What are some common challenges CUDA software engineers face when optimizing code for GPU performance?

Cuda Software Engineers often encounter challenges related to memory management, such as minimizing data transfers between CPU and GPU and optimizing memory access patterns to avoid bottlenecks. Additionally, ensuring code scalability across different GPU architectures and achieving efficient parallelization can be complex. Collaborating closely with data scientists, hardware engineers, and other developers is essential to troubleshoot performance issues and maximize throughput in real-world applications.

What are popular job titles related to Cuda Software Engineer jobs?

For Cuda Software Engineer jobs, the most frequently searched job titles are:

Infographic showing various Cuda Software Engineer job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.

Senior System Software Engineer, Performance - CUDA Driver

Santa Clara, CA • On-site

Nvidia Corporation
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidia Corporationexternal

Full-time

Re-posted 21 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

Job description

We are looking for senior systems software engineers to make the CUDA Driver faster, more efficient, and ready for the next generation of accelerated computing. Our team develops performance-critical CUDA Driver features and systems software improvements that help AI, deep learning, HPC, and other CUDA-powered applications realize more of the performance available from NVIDIA GPUs!
Some of the hardest performance problems emerge not within one component, but at the boundaries among systems software, CPUs, interconnects, and GPUs. In this role, you will trace those problems from real workloads through the software and hardware stack, design and ship production features, and deliver validated optimizations for current and emerging platforms.
You will combine hands-on engineering with broad technical influence, collaborating across CUDA software, hardware architecture, frameworks, applications, product, and customer-facing teams. You will lead cross-layer investigations, mentor engineers, and help set performance direction. Your work will help developers get more useful computing from NVIDIA GPUs today while helping shape the CUDA software and GPU architectures NVIDIA builds next.
What you'll be doing:
  • Develop and ship performance-centric CUDA Driver features and programming-model capabilities from design through validation.

  • Diagnose complex performance problems through workload analysis, focused measurement and modeling, cross-layer root-cause isolation, and application-level validation.

  • Optimize critical CUDA primitives, memory management and movement, CPU-GPU coordination, and interconnect paths for latency, throughput, bandwidth, efficiency, and scalability.

  • Establish performance goals for current and future platforms, characterize as new platforms come online, close software and hardware gaps, and drive performance readiness through releases.

  • Translate workload and platform evidence into CUDA API, programming model, system software, and future GPU architecture recommendations.

  • Set subsystem performance direction and mentor engineers tackling complex systems and performance challenges.

  • Influence technical decisions with clear performance evidence and tradeoffs and strengthen implementations through rigorous design and code reviews.

What we need to see:
  • A BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field-or equivalent practical experience - with at least 7+ years of relevant systems-software development experience.

  • Strong production C/C++ systems-programming experience, including delivery of substantial features, optimizations, or production fixes in a complex codebase.

  • Strong operating systems and concurrency foundations, including threads, synchronization, processes, virtual memory, and user/kernel interactions.

  • Strong computer architecture foundations, including processors, memory hierarchy, caching and coherence, data movement, and system interconnects.

  • Demonstrated success improving real software performance: measuring behavior, identifying bottlenecks, implementing optimizations, and profiling to prove their effectiveness.

  • Sound technical judgment, ownership of ambiguous problems, and clear communication across organizational and disciplinary boundaries.

  • Direct CUDA or GPU experience is valuable but is not required when accompanied by deep systems software, operating systems, computer architecture, and performance-engineering foundations.

Ways to stand out from the crowd:
  • Experience developing GPU or accelerator drivers, runtimes, kernel software, firmware, compilers, or other performance-critical low-level systems.

  • Experience with pre-silicon analysis, platform bring-up, performance modeling, or hardware/software co-design.

  • Systems-level performance experience with AI/DL, HPC, graphics, automotive, robotics, or similarly demanding workloads.

  • Evidence of technical inventions such as software-performance patents, novel production designs, or measurement-backed recommendations that influenced hardware revision or future architecture.

  • Python or another scripting language used for focused experimentation, data analysis, or visualization.

#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 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 September 6, 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.

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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

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