ZipRecruiter

Log In

1

Internship High Performance Computing Engineer Jobs in San Jose, 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 ...

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 ...

previous pagenext page

Showing results 21-40

All JobsHigh Performance Computing Engineer JobsInternship High Performance Computing Engineer JobsInternship High Performance Computing Engineer Jobs in San Jose, CA

Internship High Performance Computing Engineer information

See San Jose, CA salary details

$12

$70

$114

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

As of Aug 23, 2026, the average hourly pay for internship high performance computing engineer in San Jose, CA is $70.44, according to ZipRecruiter salary data. Most workers in this role earn between $57.74 and $79.71 per hour, depending on experience, location, and employer.

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.

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 are the most commonly searched types of High Performance Computing Engineer jobs in San Jose, CA?

The most popular types of High Performance Computing Engineer jobs in San Jose, CA are:

What are popular job titles related to Internship High Performance Computing Engineer jobs in San Jose, CA?

For Internship High Performance Computing Engineer jobs in San Jose, CA, the most frequently searched job titles are:

What job categories do people searching Internship High Performance Computing Engineer jobs in San Jose, CA look for?

The top searched job categories for Internship High Performance Computing Engineer jobs in San Jose, CA are:

What cities near San Jose, CA are hiring for Internship High Performance Computing Engineer jobs?

Cities near San Jose, CA with the most Internship High Performance Computing Engineer job openings:

Internship High Performance Computing Engineer jobs near you
Infographic showing various Internship High Performance Computing Engineer job openings in San Jose, CA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, 3% Contract, and 1% Nights. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $146,521 per year, or $70.4 per hour.

NVIDIA Spring 2027 Internships: Developer and Performance Technology

Nvidia Corporation

Santa Clara, CA • On-site

$164K/yr

Full-time

Posted 4 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies

Job description

By submitting your resume, you acknowledge that your 2027 Developer and Performance Technology internship application will be processed in accordance with NVIDIA's Applicant Privacy Policy and you agree to our Terms of Service. We'll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities.
NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society - from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create. Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry-leading Deep Learning teams. We're seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve.
Throughout the 8-12-month full-time internship, students will work on projects that have a measurable impact on our business. We're looking for students pursuing a B.S. or M.S. degree within a relevant or related field.
Potential Internships in this field include:
Performance Engineering
  • Running performance, image quality, and power tests for Professional Visualization, AI, and LLM benchmark applications on various GPUs; Configuring computer systems with appropriate hardware and software to run benchmarks
  • Building automation scripts to benchmarking procedure and balancing configuration files; assembling computer hardware, developing and running automation scripts on applications, and designing tools
  • Course or internship experience related to the following areas could be required: Linux and Shell Scripting, GPU Accelerated Deep Learning Frameworks (TRT, Torch, DML), Python, Containers (Docker or Singularity), Embedded Platforms, 3D Graphics, GPU Programming (CUDA, OpenCL), Benchmarking, Image Quality and Power Testing, Scripting, Debugging, Low Level System Configuration (BIOS Configurations, Memory Timing, Controlling Cache Latency, Overclocking)

Platform Performance and Power
  • Completing post-silicon performance and power benchmarking on NVIDIA and competitive GPU products; Compiling and analyzing data for internal software, hardware, sales, and marketing groups to inform decisions
  • Developing, implementing, and maintaining test systems by configuring hardware, operating systems, drivers, and software tools used for benchmarking and data collection; Implementing hands-on tests focused on performance and power for GPU platforms; Maintaining automation tools to improve testing efficiency
  • Course or internship experience related to the following areas could be required: Linux, Python Scripting, Debugging, Electrical Fundamentals (Power Measurement; Multimeters or Data Acquisition Tools), MMs, Agilent DAQs, National Instruments DAQs, GPU Programming (CUDA, OpenCL), Embedded Platforms, Benchmarking, Power Testing

Deep Learning and High-Performance Computing (HPC)
  • Planning and executing GPU performance benchmarking across a wide range of HPC and DL Frameworks and Applications; Aggregating, analyzing, and generating written and visual reports with testing data for internal teams
  • Writing scripts to improve data gathering through automation, designing efficient processes for testing a wide variety of applications and hardware; Assisting with the development of tools and processes to improve performance of automated testing
  • Course or internship experience related to the following areas could be required: GPU-Enabled Deep Learning Frameworks (TensorFlow, PyTorch, MXNet, TensorRT), GPU-Enabled HPC Applications (LAMMPS, GROMACS, Amber, RTM), GPU/CPU Benchmarking (Coud Solutions i.e. AWS, GCP, Azure), GPU Programming (CUDA, OpenACC, OpenCL), Compilers (GNU, Intel Composer, PGI), Clusters (Slurm, Kubernetes)

What we need to see:
  • Must be actively enrolled in a university pursuing a B.S. or M.S. degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, for the full 8-12-month duration of the internship; anticipated graduation date (month and year) must be clearly indicated on a resume or CV to be considered.
  • Developer and Performance Internship Preferred Start Dates: February 2027 or May 2027

Depending on the internship role, prior experience or knowledge requirements could include the following programming skills and technologies:
  • GPU Accelerated Deep Learning Frameworks (TensorFlow, PyTorch, MXNet, TensorRT, Torch, DML), GPU Programming (CUDA, OpenCL), HPC Applications (LAMMPS, GROMACS, Amber, RTM), Linux, Python/Unix Shell Scripting, Containers (Docker or Singularity)
  • 3D Graphics, Image Quality and Power Testing, Low Level System Configuration (BIOS Configurations, Memory Timing, Controlling Cache Latency, Overclocking), Electrical Fundamentals (Power Measurement; Multimeters or Data Acquisition Tools), Compilers (GNU, Intel Composer, PGI), Clusters (Slurm, Kubernetes), Embedded Platforms, Debugging, Benchmarking, Power Testing

Click hereto learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors.
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.
You will also be eligible for Intern benefits.
Applications are accepted on an ongoing basis.
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

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

View All Nvidia Jobs

Apply