NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. As part of the CAD team, our engineers develop and support tools for all of NVIDIA's semiconductor products. They also develop in-house tools in the area of Design for Test (DFT) using C++, Python, and TCL. You will work on infrastructure and software used to test our complex semiconductor devices. Below are some of the team's activities. We are a diverse team needing someone who is not afraid of a challenge. If this is you, come join us today. What you will be doing: Be responsible for designing and managing the DevOps workflow for the software team. Provide essential software, hardware, and lab support to ensure smooth operations and resolve any critical issues. Architect highly automated and customizable design flows using software engineering and AI Code Generation with modular design and object-oriented techniques. Support development of tools using C++/Python/TCL. Work cross-functionally with DFT Methodology, Implementation, and design teams with important DFT development tasks. Implement and maintain CI/CD pipelines for DevOps processes. Manage cloud infrastructure and on-premise systems for scalable and reliable deployment. Troubleshoot and resolve system, network, and application issues. What we need to see: A BE or BTech or MTech in Computer Science, Electronics Engineering, Electrical Engineering, or equivalent experience. At least 2+ years of relevant work experience in DevOps, with a focus on CI/CD, automation, and infrastructure management. Solid programming and scripting skills in Python/C++ or TCL desired. Strong software engineering skills: software design, algorithms, and QA. Strong experience with configuration management tools like Ansible, Puppet, or Chef. Proficiency with containerisation technologies such as Docker and Kubernetes. Experience with cloud platforms like AWS, Azure, or GCP. Strong knowledge in GitLab pipelines. Familiarity with tools like Artifactory and Jenkins, which are essential for managing binary repositories and automating builds and deployments. Good understanding of build frameworks such as CMake and Meson is required. Familiarity with JIRA for project and issue tracking is good to have. Experience in providing lab software and hardware Ways to stand out from the crowd: Knowledge or experience with DFT Strong GenAI, LLM, AI Code Generation skills desirable. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us. If you're creative and autonomous, we want to hear from you! #LI-Hybrid