Senior DevOps And Automation Engineer, Fabric Networking - GPU

at Nvidia
📍 Santa Clara, United States
USD 144,000-270,200 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Ansible @ 7 Grafana @ 3 Linux @ 4 Prometheus @ 3 DevOps @ 4 Python @ 7 CI/CD @ 4 Leadership @ 4 Communication @ 4 Networking @ 6 Design Patterns @ 4 GPU @ 4

Details

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.

Join our team of innovative engineers who develop and maintain software facilitating GPU communication, driving groundbreaking solutions in High Performance Computing and Deep Learning. We are seeking a DevOps and Automation Engineer to join our dynamic software infrastructure team. In this role, you will help streamline the development and operation of large-scale GPU clusters connected via NVLink and InfiniBand, supporting some of the most advanced workloads in HPC and AI.

Responsibilities

  • Drive robust CI/CD workflows to support continuous integration, build, and deployment processes across large-scale environments.
  • Streamline and enhance release management through strategic automation, orchestration, and intelligent dependency handling.
  • Improve development velocity by decoupling applications and enabling independent release cadences.
  • Design and develop automation tools for deploying, provisioning, and maintaining large GPU clusters interconnected via NVLink and InfiniBand.
  • Implement modern DevOps technologies to automate software updates, perform system maintenance, and monitor cluster health and availability.
  • Own and resolve daily operational issues in GPU clusters, ensuring high availability and performance through proactive troubleshooting.
  • Manage seamless software and firmware rollouts and rollbacks across cluster infrastructure, minimizing disruptions.
  • Collaborate across dynamic engineering and product teams in multiple time zones to align cluster operations with project goals and timelines.

Requirements

  • BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
  • 5+ years of experience managing clusters, servers, and networking infrastructure.
  • Strong scripting and automation skills with Ansible, Python, and Shell.
  • Proven experience building enterprise-grade CI/CD pipelines.
  • Understanding of modern application design patterns, including strategies for migrating and decoupling legacy code.
  • Solid understanding of Linux systems, networking, and distributed system design.
  • Strong cross-functional communication and collaboration skills.

Ways to Stand Out from the Crowd

  • Experience with Slurm or similar workload/resource managers.
  • Hands-on experience with NVIDIA DGX systems and GPU-based compute clusters.
  • Familiarity with building metrics and alerting systems (e.g., Prometheus, Grafana). Demonstrated leadership in DevOps process improvement and team productivity initiatives.