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Parallel Programming Internship Jobs in Stanford, CA

Nvidia

Senior AI Compiler Engineer, MLIR

Santa Clara, CA

$143K - $189K/yr

... parallel computing. More recently, GPU deep learning ignited modern AI - the next era of computing ... programming experience. * A track record of mentoring early career engineers and interns is a bonus ...

New

Amazon

SDE II, Neuron Infra Services

Cupertino, CA · On-site

BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ ... programming language - Knowledge of system performance, memory management, and parallel computing ...

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Parallel Programming Internship information

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$27

How much do parallel programming internship jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for parallel programming internship in Stanford, CA is $20.06, according to ZipRecruiter salary data. Most workers in this role earn between $16.92 and $22.60 per hour, depending on experience, location, and employer.

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 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 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 job categories do people searching Parallel Programming Internship jobs in Stanford, CA look for?

The top searched job categories for Parallel Programming Internship jobs in Stanford, CA are:

What cities near Stanford, CA are hiring for Parallel Programming Internship jobs?

Cities near Stanford, CA with the most Parallel Programming Internship job openings:

Parallel Programming Internship jobs near you

Senior AI Compiler Engineer, MLIR

Nvidia

Santa Clara, CA

$143K - $189K/yr

Full-time

Posted 3 days ago

New

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies

Job description

NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. 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".

NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning-from LLMs and generative AI to recommendation, vision, and speech. On this team, you'll build an MLIR-based AI compiler that powers NVIDIA's inference engine end to end, with a focus on performance, fast builds, low memory use, and Ahead-of-Time and Just-in-Time usability across data center and edge.

What you'll be doing:

  • Develop MLIR-based graph representations and optimizations for future GPU architectures.

  • Partner with framework and hardware teams to enable new model patterns and upcoming GPU architectural features.

  • Define APIs and MLIR dialects, conduct performance optimizations and analysis, implement compiler optimizations and kernel generation for neural networks, and contribute to other general software engineering work.

What we need to see:

  • Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, a related field, or equivalent experience.

  • 3+ years of relevant work or research experience in performance analysis and compiler optimizations.

  • Experience with compiler technologies such as MLIR, XLA, and LLVM.

  • Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and testing.

  • Ability to work independently, define project goals and scope, and lead your own development efforts.

  • Strong interpersonal skills and the ability to thrive in a fast-moving, dynamic, product-oriented team.

Ways to stand out from the crowd:

  • Understanding of deep learning models, algorithms, and frameworks such as PyTorch and JAX.

  • Experience with GPU kernel generation targeting high performance and fast build times.

  • Proficiency in GPU architecture with CUDA or OpenCL programming experience.

  • A track record of mentoring early career engineers and interns is a bonus

With competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, 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 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 18, 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

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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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