Deep Learning Infrastructure Engineer

We are now looking for a Deep Learning Infrastructure Engineer!NVIDIA's Deep Learning Libraries Group is seeking excellent software engineers to enable the next wave of NVIDIA’s highest performing deep learning libraries. The role spans multiple products, including TensorRT and cuDNN. The mission is to design and develop scalable, modular infrastructure that streamlines development, build, and test across NVIDIA’s diverse set of platforms, from Drive AGX for autonomous vehicles to DGX servers for datacenters and large language models. Join our technically diverse team of software engineers and infrastructure experts to design the systems that enable NVIDIA to stay ahead of the competition as we deliver the world's fastest deep learning platforms.What you'll be doing:Designing and developing software for testing and analysis of our codebasesBuilding scalable automation for build, test, integration, and release processes for publicly distributed deep learning librariesDeveloping throughout the software stack, from the user experience down to the cluster and database layersConfiguring, maintaining, and building upon deployments of industry-standard tools (e.g., Kubernetes, Jenkins, Docker, CMake, Gitlab, Jira, etc)Advancing state of the art in those industry-standard toolsWhat we need to see:BS or equivalent experience or higher degree in Computer Science or Computer Engineering2+ years of relevant experienceStrong programming skills in Python (or similar) and familiarity with C/C++ developmentExperience setting up, maintaining, and automating continuous integration systemsFluency in SCM (e.g., Git) and build systems (e.g., Make, CMake, Bazel)A pragmatic approach to solving problems and collaborationPassion for “it just works” automation and enabling team membersWays to stand out from the crowd:Background with designing and developing automation in Jenkins/Kubernetes with Groovy (or similar)Experience designing and developing unit and integration test frameworksHands-on experience with code coverage and static code analysis toolsExperience with mobile/embedded platforms and multiple operating systems (Ubuntu, RedHat, Windows, QNX, L4T, or similar)Track record of identifying useful new technologies and incorporating them into SW development flowsThis is an opportunity to have a wide impact at NVIDIA by improving development velocity across our many deep learning software projects. Are you creative, driven, and autonomous? Do you love a challenge? If so, we want to hear from you!