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Cuda Engineer Jobs in California (NOW HIRING)

Nvidia

System Software Engineer - CUDA Chips

Santa Clara, CA · On-site

$203K - $240K/yr

We are hiring engineers to work on the CUDA driver, a core component of our platform for accelerating general purpose computation on the GPU. Our team delivers features and improvements to better ...

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Cuda Engineer information

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$36K

$105.9K

$135.7K

How much do cuda engineer jobs pay per year?

As of Sep 12, 2026, the average yearly pay for cuda engineer in California is $105,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,300.00 and $134,200.00 per year, depending on experience, location, and employer.

What is a CUDA engineer?

CUDA Engineers are software developers who specialize in using NVIDIA's CUDA (Compute Unified Device Architecture) platform to write programs that run on Graphics Processing Units (GPUs). They optimize and accelerate computational tasks by parallelizing code, making use of GPUs’ capabilities for high-performance computing. CUDA Engineers often work in fields like machine learning, scientific computing, and graphics, where large amounts of data need to be processed quickly. Their expertise includes proficiency in C/C++, CUDA programming, and understanding GPU hardware and parallel computing concepts.

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

To thrive as a CUDA Engineer, you need a strong proficiency in C/C++ programming, parallel computing concepts, and deep knowledge of GPU architectures, often supported by a computer science or engineering degree. Experience with NVIDIA CUDA Toolkit, profiling/debugging tools, and sometimes certifications like NVIDIA DLI are highly valuable. Strong problem-solving, attention to detail, and effective communication skills help you optimize code and collaborate across teams. These skills ensure efficient development of high-performance GPU applications and successful project delivery in compute-intensive fields.

What are some common challenges faced by CUDA engineers when optimizing GPU-accelerated applications?

CUDA Engineers frequently encounter challenges such as managing memory effectively between the host and the device, optimizing kernel performance, and minimizing data transfer bottlenecks. Debugging parallel code can also be complex due to race conditions and the difficulty of reproducing timing-related bugs. Collaborating closely with software developers and data scientists is essential to ensure that GPU resources are leveraged efficiently and that the application's overall performance meets project goals.

What is the difference between Cuda Engineer vs GPU Developer?

AspectCuda EngineerGPU Developer
Required CredentialsBachelor's or Master's in Computer Science, Engineering, or related; knowledge of CUDA, C++, parallel programmingBachelor's or Master's in Computer Science, Engineering, or related; experience with GPU programming, CUDA, OpenCL
Work EnvironmentResearch labs, tech companies, hardware firms focusing on GPU accelerationSoftware development teams, gaming, AI, scientific computing sectors
Employer & Industry UsageHardware manufacturers, AI companies, high-performance computing firmsGame development, scientific research, machine learning applications

While both roles involve GPU programming and CUDA expertise, a Cuda Engineer primarily focuses on developing and optimizing CUDA-based solutions for hardware acceleration. In contrast, a GPU Developer works on broader GPU programming tasks, including application development across various platforms. The roles often overlap but differ in scope and specific focus areas.

What are popular job titles related to Cuda Engineer jobs in California?

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

What job categories do people searching Cuda Engineer jobs in California look for?

The top searched job categories for Cuda Engineer jobs in California are:

What cities in California are hiring for Cuda Engineer jobs?

Cities in California with the most Cuda Engineer job openings:

Cuda Engineer jobs near you
Infographic showing various Cuda Engineer job openings in California as of September 2026, with employment types broken down into 1% Internship, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $105,877 per year, or $50.9 per hour.

Senior Software Engineer CUDA UMD - GPU Kernel Scheduling

Santa Clara, CA • On-site

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

$143K - $189K/yr

Full-time

Posted 9 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

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. We're looking to grow our company, and form teams with the smartest people in the world.

Join us at the forefront of technological advancement. Are you a motivated system software engineer with a deep understanding of device drivers who has phenomenal C/C++ skills. If so, this role might be for you.

We are looking for a seasoned software professional to work on the CUDA Driver, a core component of our platform for accelerating general purpose computation on the GPU. You will be an integral part of a team that delivers features and improvements to better realize the potential of NVIDIA hardware for a growing range of computational workloads, ranging from deep learning, scientific computation, data science and self-driving cars to video games and virtual reality. What you'll be doing: As a member of our team, you will use your design abilities, coding expertise, and creativity to deliver the best compute platform in the world.

You will craft elegant solutions to exciting problems and shape the future direction of CUDA as you collaborate with your peers across NVIDIA. Evangelize, architect, and implement new features Coordinate and drive development efforts across multiple teams Help define forward-looking improvements to the CUDA APIs and programming model Extend important CUDA programming models and functionality such as CUDA Graphs Explore ways to use Graphs to improve the scheduling of AI/ML workloads on our GPUS to be more efficient and faster. Write effective, maintainable, and well-tested code Develop code for multiple operating systems What we need to see: BS or MS degree in Computer Science, Electrical Engineering or related field (or equivalent experience) Strong C and C++ programming skills Minimum of 4 years of related development experience (multiple positions for varying experience levels open) Experience driving projects across multiple teams Experience working with large codebases Background with operating system interfaces for threads, process control, and virtual memory Understanding of system level architecture, such as interconnects, memory hierarchy, interrupts, and memory-mapped IO Experience writing and debugging multithreaded programs Good written communication as well as presentation skills Ways to stand out from the crowd: Prior experience with parallel computing - preferably writing CUDA Programs or Libraries that use CUDA Knowledge of memory coherence and consistency models Background with kernel mode development Experience with Linux Systems Software development Experience maintaining and extending programming models or higher-level language support for similar environments 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 for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until September 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.

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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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