You should be pursuing a degree in a relevant field, have C/C++ skills, experience with MLIR/LLVM/XLA/TVM, open-source contributions, and knowledge of CPU/GPU architecture with CUDA/OpenCL.

You will analyze deep learning networks, develop compiler optimization algorithms, and collaborate on enhancing software performance with cross-functional teams in deep learning and hardware architecture.

Data

Software Engineering

Switzerland

Zurich

Large

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

Manufacturing & Electronics

NVIDIA

<div>
 We are hiring deep learning compiler engineering interns. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models, recommendation systems, speech recognition, image classification and other areas. Come join us to work with a top-notch team and have broad impact across the entire deep learning community.
 
 What you'll be doing:
 In this role, you will be responsible for analyzing deep learning networks and developing compiler optimization algorithms. You’ll collaborate with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software. The scope of these efforts includes crafting and implementing compiler and optimization techniques, performance optimization, and other general software engineering work.
 
 What we need to see:
 <ul>
 <li>Currently pursuing a Bachelor's, Master's, or PhD degree within Computer Engineering, Electrical Engineering, Computer Science, or a related field</li>
 <li>Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.</li>
 </ul>
 
 Ways to stand out from the crowd:
 <ul>
 <li>Experience with the following technologies: MLIR, LLVM, XLA, TVM, deep learning models and algorithms, and deep learning framework design.</li>
 <li>History of contributions to open-source projects.</li>
 <li>Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience.</li>
 </ul>
 
 NVIDIA is committed to encouraging 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.
</div>


 We are hiring deep learning compiler engineering interns. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models, recommendation systems, speech recognition, image classification and other areas. Come join us to work with a top-notch team and have broad impact across the entire deep learning community.
 
  What you'll be doing:
 In this role, you will be responsible for analyzing deep learning networks and developing compiler optimization algorithms. You’ll collaborate with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software. The scope of these efforts includes crafting and implementing compiler and optimization techniques, performance optimization, and other general software engineering work.
 
  What we need to see:
 
  Currently pursuing a Bachelor's, Master's, or PhD degree within Computer Engineering, Electrical Engineering, Computer Science, or a related field
  Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.
 
 
  Ways to stand out from the crowd:
 
  Experience with the following technologies: MLIR, LLVM, XLA, TVM, deep learning models and algorithms, and deep learning framework design.
  History of contributions to open-source projects.
  Knowledge of CPU and/or GPU architecture. CUDA or OpenCL programming experience.
 
 
 NVIDIA is committed to encouraging 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.



Deep Learning Compiler Intern - 2025

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Responsibilities

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NVIDIA

Mission & Purpose