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Internship High Performance Computing Engineer Jobs in Baltimore, MD

Devops Engineer

Annapolis Junction, MD · On-site

$54 - $73.75/hr

GIGATEC Engineering is seeking a DevOps Engineer to play a key role in maintaining and enhancing their High Performance Computing system infrastructure. The role involves engineering automation tools ...

Showing results 41-60

Internship High Performance Computing Engineer information

See Baltimore, MD salary details

$10

$59

$97

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

As of Sep 8, 2026, the average hourly pay for internship high performance computing engineer in Baltimore, MD is $59.72, according to ZipRecruiter salary data. Most workers in this role earn between $48.94 and $67.60 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 popular job titles related to Internship High Performance Computing Engineer jobs in Baltimore, MD?

For Internship High Performance Computing Engineer jobs in Baltimore, MD, the most frequently searched job titles are:

What job categories do people searching Internship High Performance Computing Engineer jobs in Baltimore, MD look for?

The top searched job categories for Internship High Performance Computing Engineer jobs in Baltimore, MD are:

Infographic showing various Internship High Performance Computing Engineer job openings in Baltimore, MD as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 16% Part Time, 3% Contract, and 1% Nights. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $124,223 per year, or $59.7 per hour.

Sr. HPC Systems Engineer (IT@JH Research Computing)

Johns Hopkins University

Baltimore, MD • On-site

Full-time

Re-posted 19 days ago


Johns Hopkins University rating

8.0

Company rating: 8.0 out of 10

Based on 71 frontline employees who took The Breakroom Quiz

190th of 631 rated colleges and universities


Job description

IT@JH Research Computing is seeking a Sr. HPC Systems Engineer who will design, build, and maintain advanced high-performance computing environments supporting Johns Hopkins University's research mission. This position focuses on the reliable operation, configuration, and optimization of HPC and AI systems, including multi-node CPU and GPU clusters, high-speed InfiniBand and Ethernet networks, and large-scale parallel and object storage.

The engineer implements and automates secure, efficient, and reproducible computing platforms used by faculty, researchers, and students across diverse scientific disciplines. Assignments include both ticket-based support and project-based deployments. The role operates with moderate independence, collaborating closely with the IT Architect, Research Computing, and reporting to the IT Manager for Research Computing to ensure scalable, sustainable, and high-performance systems that enable cutting-edge scientific discovery.

Specific Duties & Responsibilities Support and administer production systems used by researchers and Research Centers. Provide technical leadership/project management for system configuration, implementation, management, and user support for both new and existing systems. Research and recommend new functionality for HPC management and administration tools by exploring system-wide impacts, working with functional users to define current and future processes.

Expertise with architecting, operating, and debugging large scale HPC network and storage infrastructure, including MPI, NCCL, RDMA, Infiniband, and parallel file systems Works with scientific support specialists and assigns tasks and provides oversight as appropriate to HPC engineering team to support scientific researchers who use a broad spectrum of applications from diverse fields. Analyze results of server monitoring and implement changes to improve performance, processing, and utilization. Propose, maintain, and enforce policies, practices and security procedures.

Provide break/fix support, setup/installation support, escalation support, and solutions support. Collaborate closely with a variety of stakeholders, both internal and external, on all aspects of projects. Other duties as assigned.

In Addition to the Duties Described Above Deploy, configure, and maintain large-scale Linux-based HPC clusters comprising CPU and GPU nodes, high-speed interconnects, and parallel file systems. Implement and optimize workload schedulers (Slurm) and job submission policies to maximize system throughput and fair-share usage. Administer and monitor distributed storage systems (GPFS, Lustre, WekaFS, Ceph, MinIO) to ensure reliability and performance across multi-petabyte environments.

Maintain high-speed fabric and network infrastructure (Infiniband, Ethernet) to support low-latency data transfer and MPI workloads. Support research groups in deploying, testing, and optimizing scientific applications and AI/ML workflows on shared computing resources. Develop and maintain automation and monitoring frameworks for system provisioning, metrics collection, and alerting (Prometheus, Grafana, ELK).

Participate in capacity planning, hardware lifecycle management, and evaluation of new technologies in collaboration with architects and management. Ensure security and compliance through configuration hardening, patch management, and integration with campus identity and access control systems. Document system designs, procedures, and troubleshooting guides to support knowledge transfer and team continuity.

Contribute to a collaborative engineering culture that emphasizes service quality, innovation, and continuous improvement in research computing operations. Minimum Qualifications Bachelor's degree. Six years of related experience.

Additional education may substitute for required experience and additional related experience may substitute for required education beyond a high school diploma/graduation equivalent, to the extent permitted by the JHU equivalency formula. Preferred Qualifications Eight plus years of experience in high-performance computing systems administration or engineering, including experience with cluster management, workload scheduling (e.g., Slurm), and distributed or parallel storage. Deep proficiency in Linux systems administration, configuration management (Ansible, Puppet, or Salt), performance monitoring, and tuning for HPC workloads

Experience with high-speed interconnects (Infiniband, 100/400 Gb Ethernet) and parallel file systems (e.g., GPFS, Lustre, BeeGFS, or WekaFS). Working knowledge of containerization and orchestration (Singularity, Docker, Kubernetes for HPC). Ability to automate deployments and routine operations through scripting (Bash, Python)

Familiarity with data-center operations, GPU acceleration, and research software environments (e.g., CUDA, MPI, AI/ML frameworks). Strong analytical and troubleshooting skills, with proven ability to support complex research workloads in multi-user, multi-tenant environments. Experience collaborating with faculty and research groups to translate scientific requirements into practical and performant computing solutions

Classified Title: Sr. HPC Systems Engineer Role/Level/Range: ATP/04/PF Starting Salary Range: $85,500 - $149,800 Annually (Commensurate w/exp.) Employee group: Full Time Schedule: Mon-Fri, 8:30am-5pm FLSA Status: Exempt Location: Johns Hopkins Bayview Department name: IT@JH Research Computing Personnel area: University Administration.


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About Johns Hopkins University

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Gilman believed that teaching and research go hand in hand—that success in one depends on success in the other—and that a modern university must do both well. He also believed that sharing our knowledge and discoveries would help make the world a better place. In 145 years, we haven’t strayed from that vision. This is still a destination for excellent, ambitious scholars and a world leader in teaching and research. Distinguished professors mentor students in the arts and music, humanities, social and natural sciences, engineering, international studies, education, business, and the health professions. Those same faculty members, along with their colleagues at the university’s Applied Physics Laboratory, have made us the nation’s leader in federal research and development funding every year since 1979. That’s a fitting distinction for America’s first research university, a place that has revolutionized higher education in the U.S. and continues to bring knowledge and discoveries to the world.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Baltimore, MD, US

Year founded

1876