AI Computing Software Intern, GPU Kernel Libraries

NVIDIA

. Develop high performance operators on NVIDIA GPUs for cuBLAS, TensorRT, cuDNN, cuSparse and cuTensor libraries .

Posted 9/23/2026full-timeShanghai • ChinaEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing high-performance GPU operators using C/C++ and Python, with a strong focus on optimizing deep learning architectures and performance. Proficient in GPU programming with CUDA and familiar with compiler technologies such as LLVM and MLIR.

Highest-signal resume keywords

C/C++ ProgrammingPython DevelopmentCUDA ProgrammingLLVM ExperienceDeep Learning Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

GPU Kernel DevelopmentPerformance AnalysisSoftware DesignAI Technology AdoptionKernel Authoring

Soft Skills

Problem SolvingCommunicationTeamwork

Tools & Technologies

CuBLASTensorRTCuDNNCuSparseCuTensor

Industry Keywords

GPU ComputingDeep Learning ArchitecturePerformance OptimizationComputer Architecture

Tech Stack

Tools & technologies

PythonC++

About the role

Key responsibilities & impact

Develop high performance operators on NVIDIA GPUs for cuBLAS, TensorRT, cuDNN, cuSparse and cuTensor libraries
Analyze the performance of various GPU kernels on existing/new architecture
Identify bottlenecks and propose creative solutions to improve GPU kernel performance
Design and develop software for kernel authoring and shipping
Adopt cutting-edge AI technologies in GPU kernel or similar development workflow
Explore computer architectures for deep learning and work at the intersection of hardware and software
Continuously explore and optimize the performance of operators and fusion operators in deep learning networks
Design and develop scalable modular infrastructure for optimized operators used in training and inference

Requirements

What you’ll need

Pursuing a B.S., M.S., or PhD degree in computer science (or similar)
Strong programming skills in C/C++ and Python development
Familiar with GPU programming model and CUDA
Good understanding about compiler technologies
Experience with LLVM and MLIR
Excellent problem solving skills
Good communication and teamwork
Internship role in GPU computing, deep learning architecture, and performance optimization

Benefits

Comp & perks

NVIDIA is widely considered to be one of the technology world’s most desirable employers
Opportunity to work with forward-thinking and hardworking people
Opportunity to work on cutting-edge AI technologies and GPU kernel development