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

As of May 29, 2026, the average hourly pay for internship high performance computing engineer in the United States is $60.11, according to ZipRecruiter salary data. Most workers in this role earn between $49.28 and $68.03 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 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 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 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.

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Internship High Performance Computing Engineer jobs near you
Infographic showing various Internship High Performance Computing Engineer job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $125,019 per year, or $60.1 per hour.
High Performance Computing (HPC) Engineer

High Performance Computing (HPC) Engineer

Federal Reserve System

Kansas City, MO • On-site

Full-time

Posted 21 days ago

Job description

Company
Federal Reserve Bank of Kansas City
When you join the Federal Reserve-the nation's central bank-you'll play a key role, collaborating with leading tech professionals to strengthen and protect our economic, financial and payments systems. We invest in contemporary and emerging technology each year to support the Federal Reserve and our economy, and we're building a dynamic and diverse team for our future.
Important Information
  • Open to US Citizens, Green Card holders or Permanent Residents with at least 3 years of residency, with the intent to become a US citizen.
  • No sponsorship is available. Candidates must have valid work authorization, without an end date, to be considered.
  • This position requires working on-site, in Kansas City, Denver, Oklahoma City or Omaha, with 5 days per month work from home flexibility. Relocation assistance is available.

About the Role
The Center for the Advancement of Data and Research in Economics (CADRE) supports data and computationally intensive research and analytics for staff in the Economic Research division of the Federal Reserve Bank of Kansas City and across the Federal Reserve System. Our services include multiple high performance computing environments, research data warehousing, and advanced analytical tools. We are an embedded technology team within the division of Economic Research, Regional, and Community Affairs.
We are seeking an experienced High Performance Computing Engineer who can plan, implement, and maintain advanced cyberinfrastructure solutions. The ideal candidate will have deep expertise in HPC architectures, parallel computing frameworks, and scientific computing applications. You will work independently while collaborating with researchers to solve complex computational challenges that support critical economic research initiatives.
Key Activities
Operations
  • Design, deploy, configure, and administer medium scale HPC clusters and associated storage systems.
  • Monitor system health, performance metrics, and resource utilization to ensure optimal operation.
  • Implement robust security protocols and perform regular maintenance including upgrades and patching.
  • Troubleshoot complex hardware and software issues in a multi-user research environment.
  • Manage job scheduling and workload optimization using tools like SLURM.
  • Administer parallel file systems (such as ceph and IBM Spectrum Scale/GPFS) and storage solutions.

Development
  • Design and implement innovative HPC solutions to address evolving research requirements.
  • Create and maintain automation scripts and tools to streamline system administration.
  • Optimize scientific applications and computational workflows for performance.
  • Implement container technologies (Docker, Singularity) for reproducible research.
  • Support GPU computing and accelerator technologies for specialized workloads.
  • Define and track performance metrics to ensure efficient current and future use of resources.

Partnership/Collaboration
  • Partner closely with researchers to understand computational needs and translate them into technical solutions.
  • Collaborate with network, security, and data center teams to ensure integrated operations.
  • Build and maintain relationships with external vendors and technology partners.
  • Participate in the HPC community to stay current with emerging technologies and best practices.
  • Serve as a technical advisor on infrastructure planning and technology roadmaps.

Documentation/Training
  • Develop comprehensive documentation for systems, policies, and procedures.
  • Create user guides and training materials for researchers utilizing HPC resources.
  • Provide mentorship to junior staff and knowledge sharing across teams.
  • Conduct workshops and training sessions on effective use of HPC resources.

Qualifications
Required
  • Bachelor's degree in computer science, engineering, mathematics, or related field, or equivalent combination of education and experience.
  • Minimum of 6 years of relevant experience in HPC administration and systems engineering.
  • Extensive experience with Linux operating systems (Red Hat/CentOS) in an HPC environment.
  • Strong command line skills and proficiency in scripting languages (Python, Bash).
  • Experience with job scheduling systems (SLURM, PBS, LSF) and resource management.
  • Knowledge of parallel file systems and storage technologies (e.g. ceph, GPFS, Lustre, BeeGFS).
  • Familiarity with parallel programming models (MPI, OpenMP) and scientific computing frameworks.
  • Experience with configuration management and automation tools (Salt, Ansible, Puppet).
  • Demonstrated problem-solving abilities and analytical thinking.

Preferred
  • Advanced degree in a computational field.
  • Experience with cloud computing platforms and hybrid HPC environments.
  • Experience with GitLab CI/CD pipelines for research software development.
  • Understanding of GPU computing and accelerator technologies (CUDA, OpenACC).
  • Experience supporting machine learning and AI workloads on HPC systems.

Additional Information
How We Work (HWW)
  • On-site: 5 days per month remote work flexibility
  • Location: Kansas City, Denver, Oklahoma City, or Omaha
  • Remote Eligible: No
  • Relocation Assistance: Yes

Salary
  • $110,300 - $155,700 / Senior Level
  • $125,200 - $176,700 / Advanced Level
  • $139,500 - $196,800 / Expert-Lead Level
  • Final offers are determined by factors including the candidate's qualifications, internal alignment considerations, district assignment, and geographic location.

Screening: US Citizens and Green Card holders or Permanent Residents with at least 3 years of residency, with the intent to become a US citizen. This position has additional screening requirements due to the information accessed while performing the job. These additional screenings would be initiated at the time of offer acceptance and could take up to a couple of months to be completed. You can begin work before the screening is completed; however, continued employment is contingent on acceptable screening results. The areas screened may include education/employment verification, criminal history, credit history, and reference checks.
Sponsorship: The Federal Reserve Bank of Kansas City will not sponsor a new applicant for employment authorization for this positionApplicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.
About Us
  • Total Rewards & Benefits
  • Who We Are
  • What We Do

Follow us on LinkedIn, Instagram, X (formerly Twitter), and YouTube #KCFedIT
Full Time / Part Time
Full time
Regular / Temporary
Regular
Job Exempt (Yes / No)
Yes
Job Category
Information Technology Family Group
Work Shift
First (United States of America)
The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.
Always verify and apply to jobs on Federal Reserve System Careers (https://rb.wd5.myworkdayjobs.com/FRS) or through verified Federal Reserve Bank social media channels.
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