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High Performance Computing Jobs in Santa Clara, CA

Actalent

Performance Modeling Architect

Santa Clara, CA · Hybrid

$200K - $500K/yr

Your contributions will play a key role in shaping future high-performance computing and intelligent processing solutions. Responsibilities * Develop system-level performance models for AI workloads ...

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Intel

Senior CPU Performance Architect

Santa Clara, CA · On-site

$196K/yr

The Role and Impact As a CPU Performance Architect, you will play a pivotal role in shaping the future of Intel's cutting-edge CPU designs, driving innovation across high-performance computing and ...

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High Performance Computing information

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How much do high performance computing jobs pay per year?

As of Sep 5, 2026, the average yearly pay for high performance computing in Santa Clara, CA is $116,851.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,900.00 and $147,900.00 per year, depending on experience, location, and employer.

What is high performance computing?

A High Performance Computing (HPC) job involves designing, managing, and optimizing advanced computing systems used for complex calculations, simulations, and data processing. Professionals in this field work with supercomputers, parallel computing frameworks, and high-speed networks to enhance computational efficiency. HPC specialists are commonly employed in scientific research, engineering, finance, and artificial intelligence to solve large-scale problems. Responsibilities often include developing algorithms, maintaining HPC clusters, and improving system performance.

What are the typical responsibilities of someone working in high performance computing?

Professionals in High Performance Computing (HPC) are often responsible for designing, implementing, and maintaining powerful computing clusters tailored for processing large data sets or running complex simulations. Daily tasks may include optimizing code and workflows for parallel environments, troubleshooting hardware and software issues, and supporting researchers or engineers in using HPC resources efficiently. Collaboration is common, as HPC specialists work closely with IT staff, domain scientists, and software developers to ensure systems meet project and organizational goals. This role provides a challenging and dynamic work environment, offering opportunities to continually learn about emerging technologies and methodologies in computational science.

What are the key skills and qualifications needed to thrive in high performance computing, and why are they important?

To thrive in High Performance Computing, you need expertise in parallel computing, computer architecture, and programming languages such as C/C++ or Fortran, often backed by a relevant degree in computer science or engineering. Familiarity with HPC cluster management, job scheduling systems (e.g., SLURM), and experience with accelerators like GPUs or cloud platforms is crucial; certifications in Linux administration or HPC technologies are advantageous. Strong problem-solving skills, attention to detail, and effective communication abilities help professionals excel in complex, collaborative environments. These qualifications enable the efficient design, deployment, and maintenance of advanced computing infrastructure to support scientific and engineering applications.

Is high performance computing still relevant?

High Performance Computing (HPC) remains highly relevant as it enables complex data processing, scientific simulations, and large-scale analytics across industries such as research, finance, and technology. HPC specialists with skills in parallel programming, cluster management, and relevant tools like MPI or CUDA are in demand to support advancements in AI, climate modeling, and big data analysis.

What are examples of high performance computing?

High Performance Computing (HPC) involves using powerful supercomputers and parallel processing techniques to solve complex computational problems. Examples include climate modeling, molecular simulations, financial risk analysis, and large-scale data processing in scientific research. HPC jobs often require knowledge of programming languages like C++ or Fortran, and familiarity with cluster management and parallel computing frameworks such as MPI or OpenMP.

What are the most commonly searched types of High Performance Computing jobs in Santa Clara, CA?

The most popular types of High Performance Computing jobs in Santa Clara, CA are:

What are popular job titles related to High Performance Computing jobs in Santa Clara, CA?

For High Performance Computing jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching High Performance Computing jobs in Santa Clara, CA look for?

The top searched job categories for High Performance Computing jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for High Performance Computing jobs?

Cities near Santa Clara, CA with the most High Performance Computing job openings:

High Performance Computing jobs near you
Infographic showing various High Performance Computing job openings in Santa Clara, CA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $116,889 per year, or $56.2 per hour.

Senior Deep Learning Performance Architect

Nvidia

Santa Clara, CA • On-site

$196K/yr

Full-time

Re-posted 23 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 now looking for a Senior Deep Learning Performance Architect! NVIDIA is seeking extraordinary architects to develop processor and system architectures that accelerate machine learning, data analytics and high-performance computing applications. This position offers the chance to create a meaningful impact in a dynamic, technology-focused company.

What you will be doing:

  • As a member of our deep learning architecture team, you will craft high performance energy efficient system and processor architectures to extend the state of the art in deep learning.

  • Prototype key deep learning and data analytics algorithms and applications.

  • Analyze trade-offs in performance, cost and power developing analytical models, simulators and test suites.

  • Analyze architecture performance and/or energy efficiency considering deep learning workloads, modeling and prototyping.

  • Collaborate across the company to guide the direction of machine learning, working with software, research and product teams.

What we need to see:

  • Master's or PhD in Computer Science, Electrical Engineering or Computer Engineering, or equivalent experience.

  • 4+ years of relevant work or research experience.

  • A strong foundation in machine learning and deep learning fundamentals to complement your expertise in computer architecture.

  • A strong background in high performance power efficient designs, energy efficient high performance computing, performance analysis and profiling to identify performance bottlenecks.

  • Fluency in programming languages such as Python, C, C++.

  • Experience and familiarity with GPU computing and parallel programming models.

  • You have firsthand work experience with analytical performance modeling, profiling, and analysis.

The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Today, NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as "the AI computing company."

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you creative and seeking new challenges? If so, we want to hear from you! Come, join our DL Architecture team and help build the real-time, cost-effective AI computing platform driving our success in this exciting and quickly growing field.

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 June 28, 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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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