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Internship High Performance Computing Engineer Jobs in Raleigh, NC

Ampere Computing LLC

Circuit Design Engineer

Durham, NC · On-site

$147K - $220K/yr

As a pioneer in the new frontier of energy efficient high-performance computing, Ampere is part of ... Electrical or Computer Engineering - Bachelor's degree & 5 years of related experience; or MS ...

Nvidia

Senior Architect, Data Center Modeling

Durham, NC

$65 - $87/hr

... high-performance computing and AI technologies. What we need to see: * Bachelors degree in Computer Science, Computer Engineering, Electrical Engineering or related fields or equivalent experience ...

VAST Data

Customer Support Engineer

Raleigh, NC · On-site

... and high-performance computing at customer sites and in the lab. You will work directly with ... Scripting and programming - bash scripting is required; must be familiar with one or more other ...

Nvidia

Senior GPU Memory Architect

Durham, NC

NVIDIA has pioneered programmable GPUs and the CUDA language and is a world leader in high-performance computing technology, with aggressive plans for future processors. This position offers the ...

UNC-Chapel Hill

HPC DevOps Engineer

Chapel Hill, NC

$45 - $61.50/hr

... High Performance Computing (HPC) as well as High Throughput Computing (HTC). Responsibilities of the HPC DevOps Engineer include leading and contributing to a variety of areas within Research ...

Nvidia

Senior System Simulation Architect

Durham, NC

... high-performance computing (HPC) workloads. * Port/extend/develop system software (firmware, OS, and drivers) to meet workload simulation needs. * Support CPU architects and performance engineers in ...

Nvidia

HPC Operations Engineer

Durham, NC · Hybrid

$67K - $90K/yr

As an HPC Operations Engineer at NVIDIA, you will play a pivotal role in ensuring the flawless operation of our high-performance computing (HPC) environment. This opportunity is outstanding as you ...

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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 Jul 30, 2026, the average hourly pay for internship high performance computing engineer in Raleigh, NC is $58.43, according to ZipRecruiter salary data. Most workers in this role earn between $47.88 and $66.11 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship High Performance Computing (HPC) Engineer, and why are they important?

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.
What are the most commonly searched types of High Performance Computing Engineer jobs in Raleigh, NC? The most popular types of High Performance Computing Engineer jobs in Raleigh, NC are:
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Internship High Performance Computing Engineer jobs near you

Senior Software Engineer, CUTLASS Platform

Nvidia

Durham, NC

$118K - $156K/yr

Full-time

Re-posted 28 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 246 rated software companies

Job description

NVIDIA's high-performance computing platforms are powering the AI revolution across many applications and industries. Within our software stack, CUTLASS stands out as a popular open-source ecosystem dedicated to high-performance linear algebra and Tensor Core primitives. Since 2017, it has provided the community with C++ and Python abstractions to implement custom matrix multiply (GEMM) and related math and deep learning computations on NVIDIA GPUs.

If you are passionate about designing abstractions for Tensor Core and related GPU hardware features in MLIR, Python, and C++ that enable writing high performance kernels, apply to join the CUTLASS team today!

What you'll be doing:

  • Develop core components of the CUTLASS platform including Tensor Core MMAs, copies, synchronization barriers, schedulers, and other GPU hardware features in CUDA C++ and CUTLASS Python DSL.

  • Contribute to the advancement of the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes.

  • Author example kernels utilizing CUTLASS abstractions to showcase the use of novel GPU hardware features that are crucial for achieving high performance.

  • Collaborate with GPU architecture, CUDA, and NVVM/PTX compiler teams to provide feedback on programming models and to assess the performance of future GPU hardware features.

What we need to see:

  • Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience).

  • 3+ years of relevant industry experience.

  • Strong proficiency in C++ programming and software design, including debugging, performance evaluation, and testing.

  • Experience working with high-performance code generation and knowledge of compiler transformations and optimizations.

  • A deep understanding of computer architecture and parallel computing programming models.

Ways to stand out from the crowd:

  • Experience writing high-performance kernels at low levels of abstractions like NVVM/ PTX for GPUs or other similar parallel processing architectures.

  • Hands-on compiler design experience, particularly in MLIR.

  • Understanding of deep learning models, algorithms, and frameworks.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hard working people in the world working for us. If you're creative, autonomous, and love a challenge, consider joining our Deep Learning Library team and help us build the real-time, cost-effective 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 5, 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

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Benefits

Hours and flexibility

Workplace

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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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