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Software Engineer Intern, AI and DL Kernel Libraries - 2027

NVIDIA· Intern
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ShanghaiinternPosted 3w ago

About the role

Internship focused on foundational library engineering for AI and deep learning kernel libraries, contributing to low-level kernels, performance primitives, and GPU-accelerated AI workloads at NVIDIA.

Responsibilities

  • Contribute to production-quality software that ships as part of NVIDIA's AI software stack, including cuDNN, FlashInfer, and optimized support for large language model inference workloads.
  • Help develop new AI systems technologies for efficient inference, with a focus on performance, scalability, maintainability, and usability.
  • Support the design, implementation, and optimization of kernels for high-impact AI workloads across LLM inference, generative AI, computer vision, autonomous driving, and recommender systems.
  • Assist in building extensible software abstractions for deep learning libraries, LLM serving engines, and runtime systems.
  • Contribute to just-in-time compilation, code generation, and runtime technologies for performance-critical GPU workloads.
  • Analyze workload performance, tune current software, and help propose improvements to future software and hardware-software interfaces.
  • Collaborate closely with engineers across deep learning frameworks, libraries, kernels, compilers, and GPU architecture teams at NVIDIA.
  • Contribute to open-source communities and ecosystem integrations where relevant, including projects such as FlashInfer, vLLM, and SGLang.

Qualifications

  • Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science, Electrical Engineering, or a related field.
  • Coursework, research, or hands-on project experience in machine learning, deep learning systems, compilers, systems software, or GPU programming.
  • Strong programming skills in C/C++ and Python.
  • Familiarity with CUDA development and GPU programming fundamentals.
  • Experience developing with or using deep learning frameworks such as PyTorch, JAX, TensorFlow, or ONNX.
  • Understanding of linear algebra, performance analysis, profiling, and code optimization.
  • Interest in software abstractions, APIs, and higher-level system architecture for performance-sensitive systems.
  • Interest in modern machine learning and inference system trends, especially around LLMs and generative AI.
  • Strong problem-solving skills, curiosity, and the ability to work effectively in a collaborative environment.

Skills

Required:C/C++PythonCUDA developmentDeep learning frameworksPerformance analysis and profilingSoftware abstractions / APIsCollaboration
Last updated Oct 2, 2026. Interested? Apply on the company site.

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