Senior Solutions Architect, First Time Deployment Validation

Nvidia

Confirmed live 2 days ago High trust

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $148,000–$235,750 / yr
Posted: 60 days ago
Freshness: Confirmed live 2 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $202k

This role $192k

$137k most similar roles pay here $253k

This role pays less than 54% of similar roles. Most pay $168,050–$235,750 — the shaded band above. At the midpoint, this role pays about $192k versus about $202k for comparable roles.

Based on 239 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Senior Solutions Architect, First Time Deployment Validation

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As a Senior Solutions Architect, First Time Deployment Validation - NVIS, you will join the First Time Deployment team to drive the validation of AI factories from initial power-on through customer handoff. You will be responsible for setting up, adjusting, and verifying multi-GPU and multi-node Linux clusters while ensuring configurations align with NCCL and collective communication patterns like AllReduce and AllToAll. Your daily work involves running and debugging AI/LLM workloads, executing benchmarks, and investigating performance issues in partnership with engineering teams. You will build observability tools, develop automation using Python and Shell, and analyze metrics to optimize throughput and latency. The role focuses on the technical challenge of validating large-scale GPU infrastructure for distributed training frameworks like PyTorch or TensorFlow to ensure systems are production-ready for external product launches.

What does a Solutions Architect earn in Remote?

Median $231100 from 71 postings across 13 companies.

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Skills

NCCL PyTorch TensorFlow Python Shell Bash Linux HPC Distributed Systems GPU Clusters AllReduce AllToAll Observability Benchmarking SRE Metrics Logging Tracing

What you'll do

Set up, adjust, and verify AI factory environments across multi-GPU and multi-node Linux clusters.
Execute, orchestrate, and analyze key AI/LLM benchmarks to validate performance and scalability.
Investigate and resolve issues when training jobs or benchmarks fail, hang, or underperform.
Build and improve observability tools including metrics, logs, traces, and dashboards for system health.
Develop Python and Shell scripts to automate benchmark execution, result collection, and regression checks.
Analyze NCCL communication patterns and collectives like AllReduce and AllToAll for distributed workloads.
Recommend optimizations for job configurations, parallelism strategies, and cluster settings to improve throughput.
Create documentation and readiness collateral to support internal teams and customer-facing handoffs.

What we're looking for

Bachelor’s degree in Computer Science, Mathematics, Engineering, Physics, or a related field.
More than 6 years of experience managing Linux-based systems in HPC, distributed systems, or AI/ML settings.
Hands-on experience running AI/ML workloads on multi-GPU and multi-node clusters with practical knowledge of NCCL.
Solid understanding of collective communication patterns like AllReduce and AllToAll for ML/LLM training.
Familiarity with LLM training and inference workflows using frameworks such as PyTorch or TensorFlow.
Proficiency in Python and Shell/Bash for scripting, automation, and tool development.
Experience crafting, executing, and interpreting performance benchmarks.
Ability to use observability data like metrics, logs, and dashboards to troubleshoot distributed workloads.

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