NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence.
We are looking for highly motivated 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 will 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
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.
Proven ability to break down monolithic systems into scalable, loosely coupled components.
Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.
Ways to stand out from the crowd:
Experience with cluster management tools like Slurm.
Familiarity with NVIDIA DGX/HGX 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 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.
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.”
