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Internship High Performance Computing Engineer Jobs in Boston, MA

HPR

Software Engineer II

Needham, MA · Hybrid

$115K - $151K/yr

Utilize your expertise in low-level programming as we advance the state of the art in high performance computing and electronic trading * Provide the necessary guidance and hands-on delivery of the ...

Winaxis

Cloud Infrastructure/AI/ML Engineer

Boston, MA · On-site

$116K - $153K/yr

Cloud Infrastructure/AI/ML Engineer (Contract, 12+ months, Hybrid) - Location : Waltham, MA (Hybrid ... in HPC (High Performance Computing), AWS, DNAnexus, AWS Sagemaker AI - Experience with cloud ...

QCi

Semiconductor Process Engineer

Bedford, MA · On-site

... high-performance computing, artificial intelligence, cyber security as well as remote sensing ... This engineer will also be responsible for the operation of all equipment used during fabrication ...

Introl

Data Center Technician

Boston, MA · On-site

$22 - $35/hr

... high-performance computing deployments, supporting the advancement of AI computing with precision, speed, and minimal downtime. Our network of 1,000+ field engineers operates globally, tackling the ...

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All JobsInternship High Performance Computing Engineer JobsInternship High Performance Computing Engineer Jobs in Boston, MA

Internship High Performance Computing Engineer information

See Boston, MA salary details

$12

$65

$106

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

As of Jun 12, 2026, the average hourly pay for internship high performance computing engineer in Boston, MA is $65.30, according to ZipRecruiter salary data. Most workers in this role earn between $53.56 and $73.89 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.
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Internship High Performance Computing Engineer jobs near you
Quantum Calibrations Intern, Quantum Computing Services

Quantum Calibrations Intern, Quantum Computing Services

QuEra Computing, Inc.

Boston, MA

$16.25 - $21.75/hr

Other

Posted 23 days ago

Job description

Job Title:                Intern, Quantum Calibrations, Quantum Computing Services 
Job Type:                 Full-time, 3-6 months
Job Location:          Boston, MA 
Reports to:            VP of Quantum Computing Services                                                                                                                             

Summary:  

QuEra is seeking motivated interns to join our growing team focused on developing the calibration and performance characterization framework for QuEra's neutral-atom quantum computers. As an intern, you will collaborate with physicists, software engineers, and hardware specialists to design benchmarking protocols, build physics-informed models of device behavior, and develop predictive tools for real-time qubit state evolution.

This internship offers a unique opportunity to gain hands-on experience at the interface of quantum hardware and data science, contributing to the development of calibration and performance characterization frameworks for scalable, reliable neutral-atom quantum computers.

This role is part of QuEra's Quantum Computing Services team and is based at QuEra's Boston headquarters. The team's mission is to develop QuEra's neutral-atom technology into cutting-edge quantum computing products and services.

Core Responsibilities

  • Develop and test data analysis routines to fit, visualize, and interpret experimental data.
  • Design and execute device benchmarking and characterization experiments.
  • Build and apply Hamiltonian learning routines to infer effective system parameters from time-evolution data.
  • Develop predictive models for key performance metrics (gate fidelity, coherence, readout error) using time-series calibration history and machine learning methods.
  • Collaborate closely with physicists, engineers, and software developers to integrate your work into QuEra's operational stack.

Qualifications

Required

  • Foundational understanding of quantum mechanics and open quantum systems at the graduate level.
  • Experience designing and analyzing experiments involving quantum or physical systems
  • Strong programming skills in Python, including familiarity with libraries such as NumPy, SciPy, Pandas, and Matplotlib.
  • Enjoys hands-on experimentation, iteration, and uncovering structure in data.
  • Strong analytical, problem-solving, and communication skills.

Preferred

  • Familiarity with quantum gate characterization protocols (randomized benchmarking, process tomography, GST) and error budget decomposition.
  • Exposure to Hamiltonian learning, system identification, or quantum noise spectroscopy methods.
  • Experience applying machine learning (Gaussian processes, time-series models, or neural networks) to physical or experimental data.
  • Exposure to laboratory instrumentation, data acquisition, or experimental control systems.

Education & Experience

  • Currently pursuing or recently completed a Master's or PhD in Physics, Applied Physics, Computer Science, Electrical Engineering, Applied Mathematics, or a related quantitative field.

QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

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