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Internship High Performance Computing Engineer Jobs in Woburn, MA

YO AI Labs

CUDA Software Engineer - Remote

Boston, MA · Remote

$60 - $100/hr

Experience with high-performance computing or GPU-accelerated applications. * Experience optimizing workloads across different GPU architectures. * Background in graphics, compute shaders, or AI/ML ...

Posted today

YO AI Labs

CUDA Software Engineer - Remote

Boston, MA · Remote

$60 - $100/hr

Experience with high-performance computing or GPU-accelerated applications. * Experience optimizing workloads across different GPU architectures. * Background in graphics, compute shaders, or AI/ML ...

Posted today

YO AI Labs

CUDA Engineering Expert - Remote

Boston, MA · Remote

$60 - $100/hr

Experience with high-performance computing or GPU-accelerated applications. * Experience optimizing workloads across different GPU architectures. * Background in graphics, compute shaders, or AI/ML ...

New

YO AI Labs

CUDA Engineering Expert - Remote

Boston, MA · Remote

$60 - $100/hr

Experience with high-performance computing or GPU-accelerated applications. * Experience optimizing workloads across different GPU architectures. * Background in graphics, compute shaders, or AI/ML ...

New

Watershed Bio

Infrastructure Engineer

Cambridge, MA · On-site

$118K - $155K/yr

They are seeking an Infrastructure Engineer to design and manage high-performance computing systems that support their biocomputing platform, ensuring it can handle the growth of biological data.

Watershed Bio

Infrastructure Engineer

Cambridge, MA · On-site

$118K - $155K/yr

The Infrastructure Engineer will design and manage high-performance computing infrastructure to support the analysis of biological data and enable technology evolution. Responsibilities : • Build ...

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All JobsHigh Performance Computing Engineer JobsInternship High Performance Computing Engineer JobsInternship High Performance Computing Engineer Jobs in Woburn, MA

Internship High Performance Computing Engineer information

See Woburn, MA salary details

$12

$65

$107

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

As of Aug 21, 2026, the average hourly pay for internship high performance computing engineer in Woburn, MA is $65.75, according to ZipRecruiter salary data. Most workers in this role earn between $53.89 and $74.42 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 job categories do people searching Internship High Performance Computing Engineer jobs in Woburn, MA look for?

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

What cities near Woburn, MA are hiring for Internship High Performance Computing Engineer jobs?

Cities near Woburn, MA 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 Woburn, MA as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 18% Part Time, and 5% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $136,753 per year, or $65.7 per hour.

CUDA Software Engineer - Remote

YO AI Labs

Boston, MA • Remote

$60 - $100/hr

Full-time

Posted 10 hours ago

Posted today

Job description

CUDA Engineering Expert

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your expertise in CUDA, C++, and GPU programming to analyze, optimize, and improve high-performance GPU kernels.

No prior AI experience is required.

Key Responsibilities

  • Analyze, profile, and optimize GPU kernels using CUDA and profiling tools.

  • Identify performance bottlenecks and develop targeted optimization strategies.

  • Refactor C++ and CUDA code for efficiency and maintainability.

  • Develop shader logic using GLSL and WebGPU.

  • Document optimization processes, findings, and performance improvements.

  • Contribute to GPU architecture and performance discussions.

  • Collaborate with remote, cross-functional teams.

Required Qualifications

  • Strong expertise in CUDA programming and GPU kernel optimization.

  • Advanced C++ development skills.

  • Hands-on experience with GLSL and WebGPU.

  • Experience using GPU profiling tools such as NVIDIA Nsight or similar.

  • Strong understanding of GPU performance and architecture.

  • Excellent analytical, problem-solving, and technical communication skills.

  • Ability to work effectively in a remote environment.

Preferred Qualifications

  • Experience with high-performance computing or GPU-accelerated applications.

  • Experience optimizing workloads across different GPU architectures.

  • Background in graphics, compute shaders, or AI/ML acceleration.