Senior Infrastructure Software Engineer, TensorRT Edge-LLM

NVIDIA•Us, CA

4d•Hybrid

About The Position

We are now seeking a Senior Infrastructure Software Engineer for NVIDIA TensorRT Edge-LLM! NVIDIA's TensorRT Infrastructure group is seeking excellent software engineers to enable the next generation of edge AI. This is an outstanding chance to define the infrastructure/DevOps landscape for an emerging product. The mission is to develop scalable, modular infrastructure that streamlines development, builds, and tests across NVIDIA’s diverse set of platforms, from Drive AGX for autonomous vehicles to Jetson AGX for robotics and edge inference applications. You will work with autonomy to design and implement the best solutions and collaborate with external partners to achieve our goals. Join our technically diverse team of software engineers and infrastructure experts to design the systems that enable NVIDIA to stay ahead of the competition.

Requirements

BS or equivalent experience or higher degree in Computer Science or Computer Engineering
7+ years of proven experience
Strong programming skills in Python (or similar) and familiarity with modern C/C++ development
Experience setting up, maintaining, and automating continuous integration systems (e.g. Jenkins, GitHub Actions, GitLab CI)
Experience administering, monitoring, and deploying systems and services on GitHub and cloud platforms (e.g. AWS, GCP, Azure)
Fluency in SCM (e.g. Git, Perforce) and build systems (e.g. CMake, Make, Bazel)

Nice To Haves

Experience in defining and owning the DevOps strategy (design patterns, reliability and scaling) for a team or organization
Deep understanding of test automation infrastructure, framework, and test analysis
Familiarity with the development model for popular LLM frameworks and libraries such as TensorRT, TensorRT-LLM, vLLM, or SGLang
Experience with mobile/embedded/automotive platforms (e.g. Ubuntu, JetPack, QNX, or similar)
Track record of identifying useful new technologies and incorporating them into SW development flows

Responsibilities

Building and maintaining infrastructure from first principles needed to deliver TensorRT Edge-LLM
Maintaining CI/CD pipelines to automate the build, test, and deployment process and improve build and test bottlenecks
Configuring, maintaining, and building upon deployments of industry-standard tools (e.g. CMake, GitLab, GitHub Actions, Kubernetes, Docker, etc.)
Developing throughout the software stack, from the user experience and user interfaces down to the cluster layers
Monitoring and configuring embedded and desktop CPU and GPU systems to ensure high CI/CD reliability
Enable performing scans and handling of security CVEs for infrastructure components