Senior AI Factory Architect - MultiGPU Deployments & Equity

NVIDIA AI; Austin (CA); On-site; USD 124,000 - 236,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a curious and motivated Senior Solutions Architect to join its Infrastructure Specialists team. You will support AI factories, run and debug AI/LLM workloads on Linux-based GPU clusters, and engage with NCCL to boost performance.

You will apply observability and automation to benchmarking, troubleshoot failing workloads, and collaborate across hardware, software, networking, and product teams to prepare AI factories for customers.

Qualifications

• Bachelor's degree in Computer Science, Mathematics, Engineering, Physics, or related field.
• 5+ years of experience managing Linux-based systems in HPC, distributed systems, or AI/ML environments.
• Hands-on experience running AI/ML workloads on multi-GPU and multi-node clusters, including some exposure to NCCL.
• Practical knowledge of collective communication patterns like AllReduce and AllToAll, and their application in ML/LLM training.
• Skilled in Python and Shell/Bash for scripting, automation, and tooling.
• Strong communication skills and the ability to work effectively with cross-functional teams.

Responsibilities

• Set up, adjust, and verify AI factory environments across multi-GPU and multi-node Linux clusters.
• Validate configurations against guidelines for NCCL, collectives, and distributed training frameworks.
• Run key AI/LLM benchmarks — setup, orchestration, result collection, and analysis.
• Investigate and address problems when training jobs or benchmarks fail, hang, or perform below expectations.
• Build and improve observability for AI factories (metrics, logs, traces, dashboards) to understand workload behavior and system health.
• Build automation using Python and Shell for conducting benchmarks, retrieving results, and completing regression checks.
• Analyze communication patterns and NCCL usage for AI/LLM workloads, concentrating on collectives such as AllReduce and AllToAll.
• Help identify and recommend improvements to job configuration, parallelism strategies, and cluster settings to improve throughput, latency, and scaling efficiency.
• Work closely with hardware, software, networking, and product teams to prepare AI factories for customer use.
• Contribute to documentation and readiness materials for internal and customer-facing teams.

Skills

Python

Shell/Bash

Linux

Distributed systems

Education

Bachelor's degree in Computer Science, Mathematics, Engineering, Physics, or related field

Tools

NCCL

Job description

NVIDIA is seeking a curious and motivated Senior Solutions Architect to join its Infrastructure Specialists team. You will support AI factories, run and debug AI/LLM workloads on Linux-based GPU clusters, and engage with NCCL to boost performance.

You will apply observability and automation to benchmarking, troubleshoot failing workloads, and collaborate across hardware, software, networking, and product teams to prepare AI factories for customers.