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Internship Nvidia Engineering Jobs (NOW HIRING)

Senior Compiler Engineer - DL

Austin, TX

$103K - $142K/yr

A track record of success in mentoring junior engineers and interns With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology ...

Senior Compiler Engineer - DL

Redmond, WA

$117K - $160K/yr

A track record of success in mentoring junior engineers and interns With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology ...

A track record of success in mentoring junior engineers and interns With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology ...

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Internship Nvidia Engineering information

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How much do internship nvidia engineering jobs pay per hour?

As of Jul 18, 2026, the average hourly pay for internship nvidia engineering in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What is the difference between Internship Nvidia Engineering vs Software Engineering Intern?

AspectInternship Nvidia EngineeringSoftware Engineering Intern
Required CredentialsEnrolled in Computer Science or related field, strong programming skillsEnrolled in Computer Science or related field, coding proficiency
Work EnvironmentResearch labs, hardware and software development teams at NvidiaSoftware development teams, tech companies or startups
Employer & Industry UsageNvidia, semiconductor and AI industryTech companies, software firms, startups
Common Search & ComparisonInternship Nvidia Engineering vs Software Engineering Intern

Internship Nvidia Engineering focuses on hardware, AI, and graphics technology within Nvidia's innovative environment, while Software Engineering Internships are broader, covering various software development roles across multiple tech companies. Both require programming skills and relevant coursework, but Nvidia internships emphasize hardware-software integration and AI applications.

More about Internship Nvidia Engineering jobs
What cities are hiring for Internship Nvidia Engineering jobs? Cities with the most Internship Nvidia Engineering job openings:
What are the most commonly searched types of Nvidia Engineering jobs? The most popular types of Nvidia Engineering jobs are:
What states have the most Internship Nvidia Engineering jobs? States with the most job openings for Internship Nvidia Engineering jobs include:
Infographic showing various Internship Nvidia Engineering job openings in the United States as of July 2026, with employment types broken down into 94% Full Time, 4% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $40,174 per year, or $19.3 per hour.
Senior Deep Learning Compiler Engineer - XLA

Senior Deep Learning Compiler Engineer - XLA

Nvidia

Redmond, WA

$117K - $160K/yr

Full-time

Posted 22 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

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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