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Applied Computing Jobs in California (NOW HIRING)

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How much do applied computing jobs pay per year?

As of Sep 2, 2026, the average yearly pay for applied computing in California is $107,350.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,400.00 and $138,200.00 per year, depending on experience, location, and employer.

What is an applied computing job?

An Applied Computing job involves using computing principles and technologies to solve real-world problems in various industries. Professionals in this field apply software development, data analysis, cybersecurity, and IT management skills to improve business operations and decision-making. These roles can be found in sectors like healthcare, finance, manufacturing, and government, where technology is integrated to optimize processes and drive innovation.

What types of projects or challenges might I encounter in an applied computing role?

In an Applied Computing position, you may work on diverse projects such as developing custom software applications, optimizing business processes with automation, analyzing data for actionable insights, or integrating new technology solutions within existing systems. Challenges often include translating organizational needs into technical requirements, staying current with rapidly evolving technologies, and collaborating closely with stakeholders across departments. You’ll typically collaborate with IT teams, subject matter experts, and sometimes clients to ensure solutions are practical and user-centered. These varied responsibilities keep the role dynamic and provide continual opportunities to expand your technical and professional expertise.

What are the key skills and qualifications needed to thrive in an applied computing position, and why are they important?

To thrive in Applied Computing, you need strong analytical abilities, problem-solving skills, and a solid background in computer science or related disciplines, often supported by a relevant bachelor's or master's degree. Familiarity with programming languages, databases, cloud platforms, and certifications like CompTIA, AWS, or Microsoft Azure is highly beneficial. Strong teamwork, effective communication, and project management skills help you excel in multi-disciplinary settings. These qualities enable professionals to design and implement effective technical solutions to complex, real-world problems across industries.

What can you do with an applied computing degree?

An applied computing degree prepares individuals for roles such as software developer, systems analyst, data analyst, or IT specialist. Graduates can work in software development, network administration, cybersecurity, or data management, often using programming languages, databases, and technical problem-solving skills.

What are popular job titles related to Applied Computing jobs in California?

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What job categories do people searching Applied Computing jobs in California look for?

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What cities in California are hiring for Applied Computing jobs?

Cities in California with the most Applied Computing job openings:

Applied Computing jobs near you
Infographic showing various Applied Computing job openings in California as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $107,350 per year, or $51.6 per hour.

Senior Software Engineer - Python Numerical Computing Libraries

Nvidia Corporation

Santa Clara, CA • On-site

$142K - $192K/yr

Full-time

Re-posted 29 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

We are looking for an experienced software professional to contribute to design and development of accelerated and distributed implementations of Python APIs for numerical computing. In the last decade, Python has become the de-facto programming language for practitioners in AI, data science and HPC, through popular frameworks such as NumPy, SciPy, TensorFlow and PyTorch. These frameworks provide an efficient high-level programming interface, allowing their users to focus on their application while providing highly optimized implementations. NVIDIA has been at the forefront of providing GPU-accelerated implementations of the fundamental components of these frameworks.
Join our dynamic team to help develop and optimize GPU-accelerated and distributed implementations of Python numerical libraries, supporting Python-based frameworks in various ecosystems. This developer will be a crucial member of a team that is working to unlock the power of distributed GPU computing for domains such as scientific computing, data analytics, deep learning, and professional graphics, running on hardware ranging from supercomputers to the cloud!
What you will be doing:
  • 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

What we need to see:
  • 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

Ways to stand out from the crowd:
  • 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

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 August 25, 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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Benefits

Hours and flexibility

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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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