Senior AI Infrastructure Engineer

NVIDIA is looking for a Senior AI Infrastructure Engineer to join our DGX Cloud group. As an engineer, you will design, build, and maintain large-scale production systems with high efficiency and availability using software and systems engineering practices.

Responsibilities:

• Design, build, deploy, and run internal tooling for large-scale AI training and Inferencing platforms built on top of cloud infrastructure.
• Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters.
• Engage in and improve the whole lifecycle of services,from inception and design through deployment, operation, and refinement.
• Support services before they go live through activities such as system design consulting, developing software tools, platforms, and frameworks, capacity management, and launch reviews.
• Maintain services once they are live by measuring and monitoring availability, latency, and overall system health.
• Scale systems sustainably through mechanisms like automation, and evolve systems by pushing for changes that improve reliability and velocity.
• Practice sustainable incident response and blameless postmortems.
• Be part of an on-call rotation to support production systems.

Requirements:

• BS degree in Computer Science or a related technical field involving coding, or equivalent experience.
• 5+ years of experience.
• Experience with infrastructure automation and distributed systems design, developing tools for running large-scale private or public cloud systems in production.
• Experience in one or more of the following: Python, Go, C/C++, Java.
• In-depth knowledge in one or more of Linux, Networking, Storage, and Containers Technologies.
• Experience with Public Cloud and Infrastructure as Code (IAAC) and Terraform.
• Distributed system experience.

Nice to Have:

• Interest in crafting, analyzing, and fixing large-scale distributed systems.
• Systematic problem-solving approach, coupled with strong communication skills and a sense of ownership and drive.
• Ability to debug and optimize code and automate routine tasks.
• Experience in using or running large private and public cloud systems based on Kubernetes or Slurm.