We are now seeking a Senior DevOps and Build Systems Engineer for NVIDIA AI TensorRT-LLM team. This is a unique opportunity to take full ownership of the critical systems that power our engineering innovation. You and the team will be responsible for the entire DevOps landscape, from our CI/CD pipelines to our build systems to product security, driving efficiency and reliability across the organization. You will work with autonomy to design and implement the best solutions and collaborate with external partners to achieve our goals. If youre passionate about infrastructure, automation, observability, and compliance, we want you with us at one of the most innovative companies in the world!What youll be doing:<ul><li>Building and maintaining infrastructure from first principles needed to deliver TensorRT LLM</li><li>Maintain CI/CD pipelines to automate the build, test, and deployment process and build improvements on the bottlenecks. Managing tools and enabling automations for redundant manual workflows via Github Actions, Gitlab, Terraform, etc</li><li>Enable performing scans and handling of security CVEs for infrastructure components</li><li>Improve the modularity of our build systems using CMake</li><li>Use AI to help build automated triaging workflows</li><li>Extensive collaboration with cross-functional teams to integrate pipelines from deep learning frameworks and components is essential to ensuring seamless deployment and inference of deep learning models on our platform.</li></ul>What we need to see:<ul><li>Masters degree or equivalent experience</li><li>3+ years of experience in Computer Science, computer architecture, or related field</li><li>Ability to work in a fast-paced, agile team environment</li><li>Excellent Bash, CI/CD, Python programming and software design skills, including debugging, performance analysis, and test design.</li><li>Experience with CMake.</li><li>Background with Security best practices for releasing libraries.</li><li>Experience in administering, monitoring, and deploying systems and services on GitHub and cloud platforms. Support other technical teams in monitoring operating efficiencies of the platform, and responding as needs arise.</li><li>Highly skilled in Kubernetes and Docker/containerd. Automation expert with hands-on skills in frameworks like Ansible &amp; Terraform. Experience in AWS, Azure or GCP</li></ul>Ways to stand out from the crowd:<ul><li>Experience contributing to a large open-source deep learning community - use of GitHub, bug tracking, branching and merging code, OSS licensing issues handling patches, etc.</li><li>Experience in defining and leading the DevOps strategy (design patterns, reliability and scaling) for a team or organization.</li><li>Experience driving efficiencies in software architecture, creating metrics, implementing infrastructure as code and other automation improvements.</li><li>Deep understanding of test automation infrastructure, framework and test analysis.</li><li>Excellent problem solving abilities spanning multiple software (storage systems, kernels and containers) as well as collaborating within an agile team environment to prioritize deep learning-specific features and capabilities within Triton Inference Server, employing advanced troubleshooting and debugging techniques to resolve complex technical issues.</li></ul>NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most experienced and hard-working people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. Come help us build the real-time, efficient computing platform driving our success in the dynamic and quickly growing field Deep Learning and Artificial Intelligence.#LI-HybridYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 144,000 USD - 230,000 USD for Level 3, and 168,000 USD - 270,250 USD for Level 4.<div><div><div><div><div><div><div>You will also be eligible for equity and <a href="https://www.nvidia.com/en-us/benefits/" target="_blank">benefits</a>.</div></div></div></div></div></div></div>Applications for this job will be accepted at least until October 24, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.