Compute Architect Intern - 2025

3 Months ago • Upto 1 Years • Research & Development

Job Summary

Job Description

NVIDIA seeks a Compute Architect Intern for GPU/Deep Learning. The intern will analyze performance of machine learning/DL algorithms on existing/new architectures, identify bottlenecks, and propose solutions. Responsibilities include prototyping key algorithms, understanding hardware/software interplay, adding capabilities to GPU architectures, and contributing to deep learning libraries. Strong programming skills (C, C++, Python), GPU computing (CUDA, OpenCL, OpenACC), HPC (MPI, OpenMP), and computer architecture experience are required. Experience with matrix multiply and convolution algorithms is also necessary. This role offers real impact in a fast-paced environment.
Must have:
  • MS/PhD in CS, EE, Math or equivalent
  • Strong programming (C, C++, Python)
  • GPU computing (CUDA, OpenCL, OpenACC)
  • HPC (MPI, OpenMP)
  • Computer architecture experience
  • Matrix multiply & convolution algorithms
Good to have:
  • Parallel programming (CUDA/OpenCL)
  • DL frameworks/fundamentals
  • MLIR or compiler development/optimization
  • Good communication & organizational skills

Job Details

We are now looking for a Compute Architect intern for GPU / Deep Learning field.

Are you passionate about exploring computer architectures for deep learning? Do you like to work at the intersection of hardware and software?  NVIDIA is seeking world class programmers and performance architects who love to squeeze out every cycle of performance from deep learning codes.  In this role, you will write code that ships in our deep learning libraries, as well as guide the direction of our future GPU architectures.  This position offers the opportunity to have real impact in a fast-moving, technology-focused company.

What you'll be doing:

  • Analyze the performance of various machine learning/DL algorithms on existing/new architectures

  • Identify bottlenecks and propose creative solutions to improve them.

  • Prototype key deep learning and data analytics algorithms and applications

  • Understand and analyze the interplay of hardware and software architectures on future algorithms and applications

  • Add new capabilities to GPU architectures

What we need to see:

  • MS or PhD in relevant discipline (CS, EE, Math) or equivalent experience

  • Strong programming skills in C, C++, or Python

  • Familiarity with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP)

  • Strong background in computer architecture

  • Experience with matrix multiply and convolution algorithms

Ways to stand out from the crowd:

  • Experience with parallel programming and CUDA/OpenCL

  • Familiar with DL frameworks/fundamentals

  • Familiar with MLIR or compiler development/optimization

  • Good communication and organizational skills

#deeplearning

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About The Company

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.

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