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Internship High Performance Computing Engineer Jobs in Connecticut

Interactive Brokers

$21.50 - $28.25/hr

Software Development Internships 2027 Application Deadline: October 1st Schedule: Full-time, onsite ... Develop high-performance, large-data research platforms * Contribute independently and ...

ApTask Global Workforce

Scientist III

Ridgefield, CT · On-site

$53.57/hr

Programming experience with Python and R for bioinformatic data analysis in unix-like systems ... Proficiency in working with high performance computing clusters (HPC) * Proficiency in biological ...

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Internship High Performance Computing Engineer information

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.

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

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Cities in Connecticut 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 Connecticut as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution.

Senior Performance Engineer ID84179

AgileEngine

Derby, CT • On-site, Remote

Full-time

Posted 17 days ago

Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE
We are looking for a Senior Performance Engineer to own and lead an enterprise-wide Performance Engineering function as a horizontal shared service across a global QSR digital ecosystem including web, mobile, kiosk, POS, loyalty, and payments systems. You will design and execute load, stress, and endurance tests using JMeter, k6, or similar tools, integrate automated performance validation into Azure DevOps CI/CD pipelines, partner with SRE and DevOps teams on chaos engineering experiments, and leverage AI-assisted workflows for performance planning and results triage.

WHAT YOU WILL DO
- Own the enterprise Performance Engineering charter as a horizontal shared service, establishing engagement models and SDLC performance-readiness standards.
- Design, script, execute, and report performance tests (load, stress, endurance, scalability) across high-volume ordering, kiosk, POS, loyalty, and payment flows.
- Identify and resolve bottlenecks across application, database, messaging, and infrastructure layers using observability signals (e.g., Dynatrace).
- Embed automated performance validation into CI/CD pipelines (e.g., Azure DevOps) with baseline and threshold gating.
- Partner with SRE/DevOps teams to define reliability targets and run controlled chaos-engineering experiments (fault/latency injection, dependency degradation).
- Define performance-readiness criteria, provide evidence-based go/no-go release recommendations, and assist with production performance-incident resolution.
- Integrate AI-assisted workflows into performance planning, test-design acceleration, and results triage while maintaining AI-consumable artifacts and safety guardrails.

MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 4+ years of experience in performance engineering or non-functional testing at enterprise scale.
- Hands-on expertise with performance testing tools (e.g., JMeter, k6, LoadRunner, NeoLoad, or OctoPerf).
- Experience with enterprise observability and cloud monitoring platforms (e.g., Dynatrace).
- Demonstrated experience integrating automated performance validation into CI/CD pipelines (e.g., Azure DevOps).
- Scripting and automation proficiency in Java, JavaScript, or Python.
- Hands-on engineering experience in cloud environments (AWS or Azure).
- Hands-on experience using AI-assisted engineering tools, including reviewing and validating AI-generated output.
- Strong communication and stakeholder leadership skills with the ability to translate technical findings into clear business impact.
- Upper-intermediate English level.

NICE TO HAVES
- Direct experience partnering with SRE/DevOps practices on chaos engineering (fault/latency injection and dependency degradation testing).
- Prior experience supporting digital platforms within quick-service-restaurant (QSR), retail, or high-volume transactional ordering ecosystems.
- Experience maintaining AI-consumable artifacts (NFRs, workload models, baselines, thresholds) and defining AI guardrails.

PERKS AND BENEFITS
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location