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Internship High Performance Computing Engineer Jobs in New York

ASCENDING

AI Endpoint Engineer

New York, NY · Remote

End User Computing Engineer, AI Enablement Remote within the United States Contract Duration: 6 ... Your focus will be to ensure seamless integration and ongoing performance of AI applications, while ...

ASCENDING LLC

AI Endpoint Engineer

Manhattan, NY · On-site +1

End User Computing Engineer, AI Enablement Remote within the United States Contract Duration: 6 ... Your focus will be to ensure seamless integration and ongoing performance of AI applications, while ...

QCi

Postdoctoral Researcher in Quantum Optics

Hoboken, NJ · On-site

$126K/yr

The successful candidate will collaborate closely with both the high-performance computing ... Required Skills and Experience - PhD in Physics, Applied Physics, Electrical Engineering, or a ...

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Internship High Performance Computing Engineer information

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
AI and FSI Developer Technology Engineer- New College Grad 2026

AI and FSI Developer Technology Engineer- New College Grad 2026

Nvidia

New York, NY

Full-time

Posted 7 days ago

Job description

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA's GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!

We're looking for an AI Developer Technology Engineer to push the limits of performance at the intersection of AI, high-performance computing, and financial markets. In this role, you'll dive deep into parallel algorithms, GPUs, and complex systems to identify and eliminate bottlenecks, unlocking the full power of the world's most advanced processing hardware. You'll collaborate with top experts across industry and academia, influence next-generation platforms, and share your insights with the global developer community. Would you enjoy solving hard technical problems, love performance tuning, and want your work to have a visible impact across an entire industry? If so, we would love to invite you to consider this role!

What you will be doing:

  • Researching, designing, and developing groundbreaking techniques to accelerate high-performance workloads for FSI-focused, pioneering AI on NVIDIA CPUs and GPUs.

  • Working with leading technical experts to analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures.

  • Profiling and eliminating performance bottlenecks across the stack: from algorithms to kernels to system-level behavior.

  • Publishing and presenting your work in conferences, talks, and blogs to educate and inspire the broader developer community.

  • Influencing the design of future hardware architectures, system software, libraries, and programming models by collaborating closely with NVIDIA research, hardware, compiler, and tools teams.

What we need to see:

  • Pursuing or recently completed a Master's or PhD degree (or equivalent experience) in Computer Science, Computer Engineering, or Electrical and Computer Engineering or related field.

  • Relevant work or research experience.

  • Experience with low-level parallel programming (e.g., CUDA).

  • Deep understanding of CPU/GPU architecture fundamentals and how they impact performance.

  • Fluency in C/C++ and solid foundations in algorithms and software design.

  • Experience improving the performance of large-scale computational applications on GPUs.

  • Good understanding of linear algebra.

  • Strong communication and organization skills, with a logical approach to problem solving and solid prioritization abilities.

Ways to stand out from the crowd:

  • Prior internship experience in a related field.

  • Experience with inference optimization techniques and deploying optimized AI models in production.

  • Experience with TensorRT, TensorRT-LLM, and cuTile.

  • Background in capital markets with exposure to systematic/algorithmic strategies or quantitative trading.

  • Experience parallelizing and optimizing machine learning methods such as decision trees, time series models, and Monte Carlo simulations as well as knowledge of financial data models, pricing and risk simulation algorithms, portfolio optimization, or other finance-focused applications and services.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 13, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

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

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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