NVIDIA is at the forefront of innovation in AI, high-performance computing, and visualization. Our invention—the GPU—has transformed modern computing and powers everything from scientific breakthroughs to autonomous vehicles. As we drive the next wave of artificial intelligence, we’re looking for outstanding engineers to join us.
We're seeking a DevOps and Automation Engineer to join our software infrastructure team. In this role, you'll build and enhance the systems that support large-scale GPU clusters—interconnected via NVLink and InfiniBand—that run today's most fast paced HPC and AI workloads.
What you’ll be doing:
Build and maintain CI/CD pipelines that support fast, reliable integration and deployment across complex systems.
Design tools and automation workflows that simplify software releases, manage dependencies, and increase reliability.
Accelerate development by modularizing systems and enabling independent release cycles.
Build infrastructure automation for provisioning, scaling, and maintaining GPU clusters.
Automate software updates and monitor system health to improve reliability and availability.
Troubleshoot and resolve operational issues across distributed infrastructure.
Manage firmware and software rollouts to minimize downtime and ensure consistency.
Work with global engineering teams to align infrastructure tools and support project achievements.
What we need to see:
BS or MS in Computer Science, Computer Engineering, or a related field—or equivalent hands-on experience.
5+ years of experience managing infrastructure or systems in high-performance or distributed environments.
Expertise in scripting and automation using Python, Ansible, and Shell.
Practical experience with modern CI/CD tools and infrastructure-as-code frameworks.
Strong understanding of Linux, networking, and distributed system design.
Ability to break down monolithic systems into scalable, loosely coupled components.
Strong cross-functional communication and collaboration skills.
Ways to stand out from the crowd:
Experience with cluster management tools like Slurm.
Familiarity with NVIDIA DGX systems and GPU-based clusters.
Knowledge of observability tools such as Prometheus and Grafana.
Proven ability to lead DevOps process improvements and drive team efficiency.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!
Top Skills
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.”
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