We are now seeking a Infrastructure 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 infrastructure/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 you're passionate about infrastructure, automation, observability, and compliance, we want you with us at one of the most innovative companies in the world!
What you'll be doing:
Building and maintaining infrastructure from first principles needed to deliver TensorRT LLM
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
Enable performing scans and handling of security CVEs for infrastructure components
Improve the modularity of our build systems using CMake
Use AI to help build automated triaging workflows
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.
What we need to see:
Masters degree or equivalent experience
Experience in Computer Science, computer architecture, or related field
Ability to work in a fast-paced, agile team environment
Excellent Bash, CI/CD, Python programming and software design skills, including debugging, performance analysis, and test design.
Experience with CMake.
Background with Security best practices for releasing libraries.
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.
Highly skilled in Kubernetes and Docker/containerd. Automation expert with hands-on skills in frameworks like Ansible & Terraform. Experience in AWS, Azure or GCP
Ways to stand out from the crowd:
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.
Experience in defining and leading the DevOps strategy (design patterns, reliability and scaling) for a team or organization.
Experience driving efficiencies in software architecture, creating metrics, implementing infrastructure as code and other automation improvements.
Deep understanding of test automation infrastructure, framework and test analysis.
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.
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-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
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.NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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NVIDIA’s invention of the GPU in 1999 sparked 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 — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
