Senior AI Compute Engineer — AI Infrastructure Lead

NVIDIA

United States

Remote

USD 148,000 - 236,000

Full time

2 days ago
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Job summary

NVIDIA is seeking a Senior AI Compute Engineer to join the Infrastructure Specialists team. You will deploy, manage, and validate AI Compute/HPC infrastructure in Linux environments for new and existing customers, and interact with customers, partners, and internal teams throughout planning and implementation.

This role demands 8+ years of deployment experience, strong Linux and scripting skills, and familiarity with schedulers like SLURM, LSF, and UGE.

Qualifications

  • 8+ years providing in-depth support and deployment services for hardware and software products.
  • Linux system administration, process management, package management, and performance optimization.
  • Cluster management and provisioning for bare-metal servers; BCM is a bonus.
  • Scripting proficiency in Bash, Python, Ansible, etc.
  • Excellent interpersonal and organizational skills; able to travel up to 20%.

Responsibilities

  • Deploy, manage, and validate AI Compute/HPC infrastructure in Linux-based environments.
  • Be the domain expert with customers during planning calls through implementation.
  • Prepare handover documentation and knowledge transfer for customer rollout.
  • Provide feedback to internal teams by logging bugs and suggesting improvements.

Skills

Linux system administration
Scripting: Bash, Python, Ansible

Education

Bachelor's degree in Computer Science / Electrical or Computer Engineering or equivalent

Tools

BCM Base Command Manager
SLURM
LSF
UGE
Kubernetes

Job description

NVIDIA is seeking a Senior AI Compute Engineer to join the Infrastructure Specialists team. You will deploy, manage, and validate AI Compute/HPC infrastructure in Linux environments for new and existing customers, and interact with customers, partners, and internal teams throughout planning and implementation.

This role demands 8+ years of deployment experience, strong Linux and scripting skills, and familiarity with schedulers like SLURM, LSF, and UGE.

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