Senior AI Compute Engineer - Nvis

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1 · Remote

This role focuses on deploying, managing, and validating AI Compute/HPC infrastructure in Linux environments for NVIDIA's customers. It involves system design, networking, automation, and customer interaction to support large-scale AI projects. The role requires strong Linux system administration, scripting, and experience with cluster management and benchmarking tools like MLPerf.

What you'd actually do

  1. Primary responsibilities will include deploying, managing, and validating AI Compute/HPC infrastructure in Linux-based environments for new and existing customers.
  2. Be the domain expert with customers during planning calls through implementation.
  3. Handover-related documentation and perform knowledge transfers required to support customers as they begin rolling out some of the most sophisticated systems in the world!
  4. Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements.

Skills

Required

  • 8+ years providing in-depth support and deployment services; solving problems for hardware and software products.
  • Knowledge and experience with Linux system administration, process management, package management, task scheduling, kernel management, boot procedures/troubleshooting, performance reporting/optimization/logging, network-routing/advanced networking (tuning and monitoring).
  • Cluster management and provisioning technologies for bare-metal servers
  • Minimum of a four-year degree from an accredited university or college in Computer Science, Electrical or Computer Engineering or equivalent experience.
  • Scripting proficiency (Bash, Python, Ansible, etc.).
  • Excellent interpersonal skills and the ability to deliver resolutions for customer issues as they arise.
  • Strong organizational skills and ability to prioritize/multi-task easily with limited supervision.
  • Experience with schedulers such as SLURM, LSF, UGE, etc.
  • Experience with benchmarking tools such as HPL, NCCL tests, MLPerf
  • Kubernetes experience.

Nice to have

  • InfiniBand experience.
  • Experience with GPU (Graphics Processing Unit) focused hardware/software.
  • Experience with MPI (Message Passing Interface).
  • Storage technologies such as Lustre or GPFS.
  • Familiarity with OEM GPU platforms
  • Base Command Manager

What the JD emphasized

  • AI Compute infrastructure
  • Linux-based environments
  • large-scale AI Compute projects
  • MLPerf

Other signals

  • AI Compute systems
  • deploying, managing, and validating AI Compute/HPC infrastructure
  • large-scale AI Compute projects
  • MLPerf