Logo of Huzzle

🚀 Internship

Software Intern, Deep Learning Libraries - Summer 2024

Logo of NVIDIA


27d ago

🚀 Summer Internship

San Francisco

AI generated summary

  • The candidate must be pursuing Masters or PhD in a relevant field, have strong programming and problem-solving skills, experience in SCM and build systems, and stand out by having expertise in parallel computing and/or compiler, devops experience, test framework development, and contributing to software projects.
  • The software intern will design and develop GPU-accelerated Deep Learning libraries, automate build and testing processes, maintain test environments, and contribute to hardware-software co-design at NVIDIA.

Summer Internship

Software EngineeringSan Francisco


  • NVIDIA's high-performance computing platforms are powering the AI revolution! Our GPUs deliver industry-leading performance on many applications including generative AI through our impressive suite of software products like TensorRT and cuDNN. Come join our team and help develop software that integrates into many of these cutting-edge AI products


  • Pursuing Masters or PhD in Computer Science, Computer Engineering or related field
  • Strong programming skills in C++
  • Strong problem-solving skills, including debugging, performance analysis, documentation, and test design
  • Experience in SCM (e.g., Git, Perforce) and build systems (e.g., Make, CMake, Bazel)
  • Ways to stand out from the crowd:
  • Experience in parallel computing and/or compiler
  • Devops experience using industry standard workflows and tools (Jenkins, Kubernetes, Docker etc.)
  • Experience designing and developing test frameworks, code coverage and/ or static code analysis tools
  • Experience as an active contributor to a software project involving many developers
  • This is an opportunity to have a wide impact at NVIDIA by improving development velocity across our many software projects. Are you creative, driven, and autonomous? Do you love a challenge? If so, we want to hear from you

Education requirements

Currently Studying

Area of Responsibilities

Software Engineering


  • Design and develop robust and scalable GPU-accelerated Deep Learning libraries using software engineering best practices
  • Build scalable automation for build, test, integration, and release
  • Maintain and test environments for new hardware, new OSes, and platforms using industry-standard tools (e.g., Kubernetes, Jenkins, Docker, CMake, Gitlab, Jira, etc.)
  • Participate in a high-energy and dynamic company culture to develop state-of-the-art software and practice hardware-software co-design


Work type

Full time

Work mode



San Francisco