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Scientific Computing Jobs in California (NOW HIRING)

NE-NERSC

HPC Scientific Support Engineer

Bodega Bay, CA · On-site

$158K - $267K/yr

S. Department of Energy Office of Science's high-performance computing center serving more than 10,000 researchers across scientific disciplines. As part of the User Engagement Group (UEG), the ...

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Scientific Computing information

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$13

$31

$51

How much do scientific computing jobs pay per hour?

As of Jun 16, 2026, the average hourly pay for scientific computing in California is $31.07, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $39.62 per hour, depending on experience, location, and employer.

What are the typical daily responsibilities of someone working in Scientific Computing?

Professionals in Scientific Computing typically spend their days developing and optimizing computational models, writing code to analyze large datasets, and running simulations on high-performance computing systems. They often collaborate closely with scientists, researchers, or engineers to interpret results and improve methodologies. Depending on the industry, they may also be responsible for documenting workflows, troubleshooting complex issues, and staying current with technological advances in their field. Daily work often involves problem-solving, technical meetings, and the continuous improvement of algorithms and computational processes.

What are the key skills and qualifications needed to thrive in the Scientific Computing position, and why are they important?

To thrive in Scientific Computing, you need a strong background in mathematics, computer science, and scientific principles, often supported by a relevant degree such as physics, engineering, or computational science. Proficiency with programming languages like Python, C++, or MATLAB, experience with high-performance computing (HPC) systems, and familiarity with scientific software and libraries are typically essential. Excellent problem-solving abilities, teamwork, and clear communication skills are important soft skills for this role. These skills enable professionals to develop efficient computational solutions, collaborate effectively across multidisciplinary teams, and drive progress in research and innovation.

What is a Scientific Computing job?

A Scientific Computing job involves using advanced computational methods, algorithms, and mathematical modeling to solve complex scientific and engineering problems. Professionals in this field develop and optimize software, perform simulations, and analyze large datasets to support research in disciplines like physics, biology, and engineering. They often work with high-performance computing (HPC) systems and programming languages such as Python, C++, or Fortran. These roles are commonly found in academia, government research labs, and industries like aerospace, pharmaceuticals, and finance.

What are the most commonly searched types of Scientific Computing jobs in California? The most popular types of Scientific Computing jobs in California are:
What are popular job titles related to Scientific Computing jobs in California? For Scientific Computing jobs in California, the most frequently searched job titles are:
What job categories do people searching Scientific Computing jobs in California look for? The top searched job categories for Scientific Computing jobs in California are:
What cities in California are hiring for Scientific Computing jobs? Cities in California with the most Scientific Computing job openings:
Scientific Computing jobs near you
Infographic showing various Scientific Computing job openings in California as of June 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $64,616 per year, or $31.1 per hour.
Senior Software Engineer - Python Numerical Computing Libraries

Senior Software Engineer - Python Numerical Computing Libraries

NVIDIA

Santa Clara, CA • On-site

$142K - $192K/yr

Full-time

Posted 13 days ago

Job description

Job Summary:
NVIDIA is a leader in GPU-accelerated computing, and they are seeking an experienced software professional to contribute to the design and development of Python APIs for numerical computing. The role involves optimizing GPU-accelerated implementations and supporting Python-based frameworks across various ecosystems.
Responsibilities:
• Work closely with product management and internal or external partners, to understand use cases and requirements, and contribute to the technical roadmaps of libraries
• Architect, prioritize, and develop accelerated and distributed implementations of numerical algorithms
• Design future-proof Python APIs for accelerated numerical/scientific computing libraries
• Analyze and improve the performance of developed APIs on various CPU and GPU architectures, especially as a part of customer-critical end-to-end workflows
• Prototype integrations of developed APIs into targeted frameworks
• Write effective, maintainable, and well-tested code for production use
• Contribute to the development of runtime systems that underlay the foundation of multi-GPU computing at NVIDIA
Qualifications:
Required:
• BS, MS or PhD degree in Computer Science, Applied Math, Electrical Engineering or related field (or equivalent experience)
• 6+ years of relevant industry experience or equivalent academic experience after BS
• Excellent Python, C++ and CUDA programming skills
• Strong understanding of fundamental numerical methods, dense and sparse array computing
• Deep familiarity with Python numerical computing libraries (e.g. NumPy, SciPy), including accelerated implementations (e.g. CuPy, Jax.NumPy, NumS, cuNumeric)
• Experience developing and publishing Python libraries, following standard methodologies for pythonic API design
• Strong background with parallel programming and performance analysis
Preferred:
• Experience using/contributing to Python libraries for data science (e.g. Pandas), machine learning (e.g. scikit-learn) and deep learning (e.g. TensorFlow, PyTorch)
• Experience with low-level GPU performance optimization
• Experience building, debugging, profiling and optimizing distributed applications, on supercomputers or the cloud
• Background with tasking or asynchronous runtimes
• Background on compiler optimization techniques, and domain-specific language design
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.
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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