Senior AI Infra Architect GPU & Cloud

Nvidia Corporation in

Washington (District of Columbia)

On-site

USD 184,000 - 357,000

Full time

3 days ago
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Job summary

NVIDIA is seeking a Senior AI Infrastructure Solutions Architect to drive GPU infrastructure deployments for Public Sector customers during the AI transformation. You will lead build and deployment, coordinate across product, engineering, and field teams, and deliver performant clusters across data centers.

The role requires travel up to 20% and strong background in accelerated computing, networking, and large-scale GPU systems.

Qualifications

  • BS/MS/PhD in Electrical Engineering, Computer Science or equivalent experience.
  • 6+ years supporting Solution Engineering or similar Architecture roles.
  • Experience with high performance Networking or CPU/GPU acceleration.
  • Familiarity with schedulers: SLURM, LSF, UGE, etc.
  • Experience with benchmarking tools: HPL, NCCL tests, MLPerf and Kubernetes.

Responsibilities

  • Lead technical discussions with customers during build, deployment, and production.
  • Serve as primary technical driver for GPU infrastructure projects across lifecycles.
  • Conduct regular technical meetings to discuss roadmap, issues, and solutions.
  • Collaborate with product, engineering, and account teams to align on strategy.
  • Analyze compute/network configurations to deliver performant clusters.
  • Create and deliver technical content such as presentations and tutorials.
  • Lead communications with customers and NVIDIA management.
  • Provide feedback to engineering for product requirements and docs.

Skills

High performance Networking
CPU/GPU acceleration
Kubernetes experience
Travel readiness

Education

BS/MS/PhD in Electrical Engineering or Computer Science

Tools

SLURM
LSF
UGE
HPL benchmarking
NCCL tests
MLPerf

Job description

NVIDIA is seeking a Senior AI Infrastructure Solutions Architect to drive GPU infrastructure deployments for Public Sector customers during the AI transformation. You will lead build and deployment, coordinate across product, engineering, and field teams, and deliver performant clusters across data centers.

The role requires travel up to 20% and strong background in accelerated computing, networking, and large-scale GPU systems.

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