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Unconventional AI

Junior System Modeling

... CUDA) or other hardware accelerators. • Prior research or internship experience in high-performance computing (HPC) or neuromorphic systems. • Contributions to open-source AI or systems software ...

Workato

Intern, AI Engineering

San Francisco, CA

... Interns in San Francisco. You'll work on fundamental problems in LLM-based agentic systems and ... Proficiency in CUDA programming and custom kernel development for LLM operations * Background in ...

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How much do cuda internship jobs pay per month?

As of Jul 14, 2026, the average monthly pay for cuda internship in the United States is $5,290.17, according to ZipRecruiter salary data. Most workers in this role earn between $3,000.00 and $7,500.00 per month, depending on experience, location, and employer.

What kind of projects or tasks can I expect to work on during a Cuda Internship?

As a CUDA intern, you’ll typically work on tasks related to developing, profiling, or optimizing GPU-accelerated applications and algorithms. Your responsibilities may include writing and testing CUDA kernels, analyzing code performance, and assisting in integrating GPU computing into software projects. You may also collaborate with experienced engineers, learn to use industry-standard tools, and participate in team meetings to discuss technical challenges or progress. This hands-on experience is designed to strengthen your technical skills while giving you insight into real-world GPU development workflows.

What is a Cuda Internship job?

A CUDA Internship is a temporary position where interns work with NVIDIA's CUDA parallel computing platform. They typically assist in developing and optimizing GPU-accelerated applications for tasks like machine learning, scientific computing, and gaming. Interns may work on improving algorithms, writing CUDA kernels, or debugging performance issues. This role requires knowledge of C/C++, GPU architectures, and parallel programming concepts. It's ideal for students or recent graduates interested in high-performance computing and GPU programming.

What are the key skills and qualifications needed to thrive in the Cuda Internship position, and why are they important?

To thrive as a Cuda Intern, you should have a solid background in computer science, strong programming skills (especially in C/C++), and foundational knowledge of parallel computing or GPU architectures. Familiarity with CUDA programming, NVIDIA development tools, and understanding of performance optimization techniques are highly valuable for this role. Strong problem-solving abilities, eagerness to learn, and good teamwork and communication skills will help you excel as an intern. These competencies enable you to contribute effectively to CUDA-based projects and adapt to the fast-paced, innovative environment often found in tech industries.

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Cuda Internship jobs near you
Senior Deep Learning Compiler Engineer - XLA

Senior Deep Learning Compiler Engineer - XLA

Nvidia

Redmond, WA • On-site

$117K - $160K/yr

Full-time

Re-posted 17 days ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 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".

We are looking for versatile software engineers for our XLA team. NVIDIA is at the center for the AI revolution that's transforming how people live, work, and interact with technology. Come join us to build high-performance, production-grade software that's at the core of next-generation AI systems.

What you will be doing:

In this role, develop compiler optimization algorithms for deep learning workloads. You will optimize inference and training performance for the JAX framework and the OpenXLA compiler on NVIDIA GPUs at scale. You'll collaborate with our partners in deep learning framework teams and our hardware architecture teams to accelerate the next generation of deep learning software. The scope of these efforts include:

  • Crafting and implementing compiler optimization techniques for deep learning network graphs.

  • Designing novel graph partitioning and tensor sharding techniques for distributed training and inference.

  • Performance tuning and analysis.

  • Code-generation for NVIDIA GPU backends using open-source compilers such as MLIR, LLVM and OpenAI Triton.

  • Designing user facing features in JAX and related libraries and other general software engineering work.

  • Working closely with GPU hardware engineering teams to design AI compiler software features for next-generation GPUs.

What we need to see:

  • Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field (or equivalent experience).

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

  • Ability to work independently, define project goals and scope, and lead your own development effort adopting clean software engineering and testing practices.

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

  • Strong foundation in architecture of CPU, GPUs or other high performance hardware accelerators. Knowledge of high-performance computing and distributed programming.

  • CUDA or OpenCL programming experience is desired but not required.

  • Experience with the following technologies is a huge plus: XLA, TVM, MLIR, LLVM, OpenAI Triton, deep learning models and algorithms, and deep learning framework design.

  • Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team. A history of mentoring junior engineers and interns is a bonus.

Ways to stand out from the crowd:

  • Experience working deep learning frameworks such as JAX, PyTorch or TensorFlow.

  • Extensive experience with CUDA or with GPUs in general.

  • Experience with open-source compilers such as XLA, LLVM, MLIR or TVM.

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.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 1, 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.#deeplearning

What Nvidia employees say

Hours and flexibility

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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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