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Internship High Performance Computing Engineer Jobs in Santa Clara, CA

RadixArk

Performance Engineer

Palo Alto, CA · On-site

... high-performance computing • Familiarity with profiling tools, performance debugging, tracing ... both engineers and customers Preferred : • Experience with CUDA, Triton, Pallas, ROCm, XLA, or ...

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Internship High Performance Computing Engineer information

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How much do internship high performance computing engineer jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for internship high performance computing engineer in Santa Clara, CA is $70.59, according to ZipRecruiter salary data. Most workers in this role earn between $57.88 and $79.90 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an internship high performance computing engineer?

To thrive as an Internship High Performance Computing Engineer, you need a solid background in computer science fundamentals, programming (especially in C/C++ or Python), and a familiarity with parallel computing concepts, often supported by coursework or relevant project experience. Experience with Linux environments, HPC clusters, and distributed computing frameworks, as well as tools like MPI, OpenMP, or Slurm, is commonly required. Strong problem-solving skills, attention to detail, and the ability to collaborate effectively within technical teams help interns stand out. These skills ensure you can efficiently support computational research, resolve technical challenges, and contribute meaningfully to HPC projects.

What is the difference between Internship High Performance Computing Engineer vs Internship Data Scientist?

AspectInternship High Performance Computing EngineerInternship Data Scientist
Required SkillsProgramming (C++, Python), parallel computing, HPC systemsStatistics, machine learning, data analysis, Python/R
Work EnvironmentResearch labs, tech companies, academia with focus on HPC systemsTech firms, finance, healthcare, research institutions
Industry UsageHigh-performance computing projects, scientific simulationsData analysis, predictive modeling, business insights

Internship High Performance Computing Engineers focus on developing and optimizing computational systems for large-scale scientific and engineering problems, requiring skills in parallel programming and HPC environments. In contrast, Internship Data Scientists analyze data to extract insights, using statistical and machine learning techniques. Both roles are valuable in tech and research sectors but differ in technical focus and daily tasks.

What is an internship high performance computing engineer?

An Internship High Performance Computing (HPC) Engineer is a student or early-career professional who works with advanced computing systems designed for processing large data sets and complex calculations at high speeds. During the internship, they assist in developing, optimizing, and maintaining HPC infrastructure, software, or applications used in scientific research, engineering, or data analysis. The role often involves learning about parallel computing, cluster management, and performance tuning, while gaining hands-on experience with cutting-edge technologies. Interns work under the supervision of experienced HPC engineers, contributing to projects that advance computational capabilities in various fields.

What types of projects can I expect to work on as an internship high performance computing engineer?

As an Internship High Performance Computing (HPC) Engineer, you will typically contribute to projects involving optimization of scientific applications, performance analysis, and cluster management. Interns often assist with benchmarking software, troubleshooting issues in parallel computing environments, and supporting researchers with technical solutions. You'll likely collaborate closely with senior HPC engineers, system administrators, and academic researchers to ensure efficient use of computing resources. This hands-on experience provides valuable insight into real-world challenges faced in HPC environments and helps build a strong foundation for future roles in the field.
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Internship High Performance Computing Engineer jobs near you
Infographic showing various Internship High Performance Computing Engineer job openings in Santa Clara, CA as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $146,827 per year, or $70.6 per hour.

Senior Deep Learning Performance Architect

Nvidia

Santa Clara, CA

$196K/yr

Full-time

Re-posted 29 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 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

Year founded

1993

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