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.
What you'll be doing:
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
What we need to see:
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)
Ways to stand out from the crowd:
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
This is an opportunity to have a wide impact at NVIDIA by improving development velocity for our rapidly growing compute software projects. Are you creative, driven, and autonomous? Do you love a challenge? If so, we want to hear from you!
#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 184,000 USD - 287,500 USD.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 an inclusive 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.Skills Required
- Bachelor's degree in Computer Science, Computer Engineering or equivalent experience
- 7+ years of proven software engineering 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)
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.
NVIDIA Insights
What We Do
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.”
