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Parallel Computing Software Engineer Jobs in California

Nvidia

System Software Engineer - GPU

Santa Clara, CA · On-site

$203.20K - $240.80K/yr

We are seeking a System Software Engineer to work on next-generation computing and graphics ... Background with Parallel Computing, PCIE, Nvlink or server product technologies like Infiniband ...

Nvidia

System Software Engineer - GPU

Santa Clara, CA · On-site

$203.20K - $240.80K/yr

We are seeking a System Software Engineer to work on next-generation computing and graphics ... Background with Parallel Computing, PCIE, Nvlink or server product technologies like Infiniband ...

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How much do parallel computing software engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for parallel computing software engineer in California is $122,612.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,391.00 and $143,457.00 per year, depending on experience, location, and employer.

What Is the Job of a Parallel Computing Software Engineer?

A parallel computing software engineer develops and updates high-performance computing software and tools to increase their efficiency. In this career, you focus on both parallel computing and parallel programming software to solve complex problems or algorithms. More specific duties and responsibilities of this job may revolve around the development of new or improved software to optimize multi-threaded systems or artificial intelligence data. As a parallel computing software engineer, you generally work on a team to build state-of-the-art technology to bring your company's systems to the forefront of the industry. The industries that use parallel computing include engineering, aircraft computing, and government agencies.

What are the key skills and qualifications needed to thrive as a Parallel Computing Software Engineer, and why are they important?

To thrive as a Parallel Computing Software Engineer, you need a solid background in computer science, strong programming skills (especially in C/C++ or Python), and expertise in parallel algorithms and data structures, typically supported by a relevant degree. Familiarity with parallel programming frameworks and tools such as MPI, OpenMP, CUDA, and experience working on distributed systems or high-performance computing platforms are essential. Strong problem-solving abilities, teamwork, and effective communication help you to collaborate on complex projects and convey technical ideas clearly. These skills are crucial for building scalable, efficient software solutions that leverage parallelism to maximize computational performance.

What are the typical daily responsibilities of a Parallel Computing Software Engineer?

As a Parallel Computing Software Engineer, your daily tasks often include designing, developing, and optimizing algorithms to run efficiently on multi-core processors or distributed systems. You’ll collaborate closely with other software engineers, data scientists, and hardware specialists to ensure applications scale effectively across multiple computing nodes. Debugging and profiling code to identify bottlenecks, maintaining high code quality, and keeping up-to-date with the latest parallel programming models and frameworks are also key parts of the role. Additionally, you may participate in code reviews and help train team members on best practices for parallelism.

What are Parallel Computing Software Engineers?

Parallel Computing Software Engineers are professionals who design, develop, optimize, and maintain software that can run simultaneously on multiple processors or computers. Their work enables applications to process large volumes of data or perform complex computations more efficiently by splitting tasks across multiple processing units. They often use technologies such as multi-threading, distributed computing frameworks, and GPU programming to maximize performance. These engineers are crucial in fields like scientific computing, artificial intelligence, and big data analytics, where processing speed and scalability are essential.
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What are popular job titles related to Parallel Computing Software Engineer jobs in CA? For Parallel Computing Software Engineer jobs in CA, the most frequently searched job titles are:
Parallel Computing Software Engineer jobs near you
Infographic showing various Parallel Computing Software Engineer job openings in California as of May 2026, with employment types broken down into 3% As Needed, 88% Full Time, 6% Part Time, and 3% Contract. Highlights an 94% Physical, 5% Hybrid, and 1% Remote job distribution, with an average salary of $122,612 per year, or $58.9 per hour.
Senior Systems Software Engineer, CUDA Driver

Senior Systems Software Engineer, CUDA Driver

NVIDIA

Santa Clara, CA • On-site

Full-time

Posted 14 days ago

Job description

Job Summary:
NVIDIA is a leader in GPU technology, driving innovation in AI and parallel computing. They are seeking a Senior Systems Software Engineer to work on the CUDA Driver, enhancing the capabilities of NVIDIA hardware for various computational tasks. The role involves collaborating with teams to design, implement, and improve features for the CUDA platform.
Responsibilities:
• 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
• Write effective, maintainable, and well-tested code
• Develop code for multiple operating systems
Qualifications:
Required:
• BS or MS degree in Computer Science, Electrical Engineering or related field (or equivalent experience)
• Strong C and C++ programming skills
• Minimum of 7 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
• Experience writing and debugging multithreaded programs
• Good written communication as well as presentation skills
Preferred:
• Prior experience with parallel computing
• Understanding of system level architecture, such as interconnects, memory hierarchy, interrupts, and memory-mapped IO
• Knowledge of memory coherence and consistency models
• Background with kernel mode development
• Experience with Linux, or Windows Systems Software development
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
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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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