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NVIDIA

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Accelerated Compute Systems Performance Architect Intern - 2027

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Summary

NVIDIA is hiring an Accelerated Compute Systems Performance Architect intern in Shanghai to analyze and optimize performance on current and next-generation NVIDIA GPUs. Day-to-day involves software-hardware co-design and cross-team collaboration, requiring CUDA/C++ programming and solid GPU/systems architecture knowledge.

We are now looking for an Accelerated Computing Architect intern. NVIDIA is developing software and hardware system architectures for accelerated high performance computing, scientific computing, machine learning, artificial intelligence, datacenter, and automotive computing. This position offers you the opportunity to make a meaningful impact in a fast-moving, technology focused company.

What you'll be doing:

  • Performing in-depth analysis and optimization to ensure the best possible performance on current and/or next-generation NVIDIA GPUs.

  • Understanding and analyzing the interplay of hardware and software architectures on core algorithms, programming models, and applications.

  • Actively collaborating with the hardware design, software engineering, product, and research teams to guide the direction of accelerated computing.

  • Diving into accelerated computing applications to facilitate software-hardware co-design.

  • Writing up and presenting your work by writing white papers, conference publications, official blog posts, patent applications, etc. as appropriate.

What we need to see:

  • Pursuing B.Sc., M.Sc., or Ph.D. in relevant discipline (CS, EE, CE).

  • A passion for performance analysis and optimization.

  • Hands-on experience with the massively parallel GPU programming model, e.g. CUDA or OpenCL. Familiarity with APIs for multi-node communication, like MPI or OpenSHMEM/NVSHMEM, is a plus.

  • Solid background in GPU and computer systems architecture.

  • Strong knowledge of C and C++ with a solid understanding of software design, programming techniques, and algorithms. Familiarity with Python is a plus.

  • Good communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. Are you creative and autonomous? Do you love the challenge of pushing an architecture to its limits? If so, we want to hear from you.

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.

What they ask for

Required

  • Pursuing B.Sc., M.Sc., or Ph.D. in a relevant discipline (CS, EE, CE)
  • A passion for performance analysis and optimization
  • Hands-on experience with the massively parallel GPU programming model, e.g. CUDA or OpenCL
  • Solid background in GPU and computer systems architecture
  • Strong knowledge of C and C++ with a solid understanding of software design, programming techniques, and algorithms
  • Good communication and organization skills, logical problem solving, good time management, and task prioritization

Preferred

  • Familiarity with APIs for multi-node communication, like MPI or OpenSHMEM/NVSHMEM
  • Familiarity with Python

Skills

See also

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