1

Parallel Programming Internship Jobs in New York

Parallel Programming Internship information

What is a parallel programming internship?

A Parallel Programming Internship is an opportunity for students or recent graduates to gain hands-on experience in developing software that can execute multiple operations simultaneously. Interns work with technologies such as multi-core processors, GPUs, and distributed computing systems to optimize code for speed and efficiency. These positions are commonly found in industries like scientific research, finance, and tech companies where high-performance computing is crucial. Interns typically gain skills in languages and frameworks like C++, Python, CUDA, OpenMP, and MPI while collaborating with experienced engineers. The experience prepares them for advanced roles in software development and high-performance computing.

What is the difference between Parallel Programming Internship vs Software Development Internship?

AspectParallel Programming InternshipSoftware Development Internship
Required SkillsParallel algorithms, C/C++, CUDA, OpenMPProgramming languages, software design, debugging
Work EnvironmentResearch labs, tech companies focusing on high-performance computingSoftware firms, startups, tech companies
Industry UsageHigh-performance computing, scientific researchWeb, mobile, enterprise applications
Common Search IntentParallel programming, HPC internshipsSoftware development, coding internships

While both internships involve programming skills, a Parallel Programming Internship focuses on high-performance computing and parallel algorithms, often requiring knowledge of C/C++ and GPU programming. In contrast, a Software Development Internship covers broader software engineering skills applicable across various industries. The choice depends on your interest in specialized parallel computing versus general software development.

What types of projects do interns typically work on during a parallel programming internship?

During a Parallel Programming Internship, interns often contribute to projects involving optimization of existing code, development of parallel algorithms, or performance analysis using multi-core processors or GPUs. You may be tasked with refactoring sequential code to run efficiently on parallel architectures, collaborating with senior engineers, and utilizing frameworks like OpenMP, MPI, or CUDA. These projects provide hands-on experience in solving computational bottlenecks and working closely with cross-functional development teams. This exposure helps build a strong foundation for further roles in high-performance computing or software engineering.

What are the key skills and qualifications needed to thrive as a parallel programming intern, and why are they important?

To thrive as a Parallel Programming Intern, you need a solid understanding of computer science fundamentals, algorithms, and concurrency concepts, often supported by coursework in parallel computing or a related field. Familiarity with programming languages such as C/C++, Python, and parallel computing frameworks like OpenMP, MPI, or CUDA is typically required. Strong analytical thinking, problem-solving ability, and effective teamwork are key soft skills for excelling in collaborative and technical environments. These skills and qualifications are vital for efficiently developing, debugging, and optimizing programs that leverage parallel architectures for improved performance.

What are the most commonly searched types of Parallel Programming jobs in New York?

The most popular types of Parallel Programming jobs in New York are:

What cities in New York are hiring for Parallel Programming Internship jobs?

Cities in New York with the most Parallel Programming Internship job openings:

Senior Math Libraries Engineer - Dense Linear Algebra

Nvidia

New York, NY • Hybrid

$110K - $149K/yr

Full-time

Posted 7 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies


Job description

We are looking for software engineers to join our development efforts in the area of dense linear algebra kernels for high-performance libraries such as cuSOLVER. Around the world, leading commercial and academic organizations are revolutionizing AI, data analytics, and scientific and engineering simulations, using data centers powered by GPUs and high-performance linear algebra libraries. Applications of these technologies include computer aided engineering (CAE), electronic design automation (EDA), quantum chemistry, autonomous vehicles, LLMs, computer vision, encryption, and countless others. Did you know our team develops the GPU accelerated libraries and SDKs that help make these possible?

In this role, you will work together with other developers on designing, developing, and optimizing kernels for various algorithms including triangular factorizations, eigenvalue decompositions and singular value decompositions. Ideal candidates will not only have experience developing accelerated computing kernels, but also be motivated to advance the state-of-the-art in a variety of accelerated computing domains. If this sounds exciting, we would love to meet you!

What you will be doing:

  • Designing, implementing and optimizing scalable high-performance numerical dense linear algebra software on GPUs

  • Providing technical leadership and guidance to library engineers, QA engineers, and interns working with you on projects

  • Working closely with product management and other internal and external partners to understand feature and performance requirements and contribute to the technical roadmaps of libraries

  • Finding and realizing opportunities to improve library quality, performance and maintainability through re-architecting and establishing innovative software development practices

What we need to see:

  • PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience)

  • 5+ years of overall experience in developing, debugging and optimizing high-performance numerical linear algebra software using C++ and parallel programming; ideally using CUDA, MPI, OpenMP, OpenACC, pthreads

  • Strong fundamentals in numerical methods such as computational linear algebra, linear system solvers, and methods for eigenvalue, singular value, and other decompositions

  • Experience developing dense linear algebra libraries such as BLAS, LAPACK; and their parallel counterparts like PBLAS and SCALAPACK

  • Strong collaboration, communication, and documentation habits

Ways to stand out from the crowd:

  • Good knowledge of CPU and/or GPU hardware architecture

  • Experience with adopting and advancing, software development practices such as CI/CD systems and project management tools such as JIRA.

  • Experience with working in a globally distributed organization

  • Strong background of large-scale computing technologies such as PDE solvers, eigenvalue solvers and time-domain simulation methods (e.g., CFD, FEA)

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing for science and engineering. More recently, GPU deep learning ignited modern AI - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company." We're looking to grow our company and build our teams with the smartest people in the world! Join us at the forefront of technological advancement.

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 9, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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