Senior Solutions Architect, First Time Deployment Validation - NVIS

About the role

The First Time Deployment Team owns first-time execution of NVIDIA's latest products and systems; gathering install and bring-up evidence, operationalizing the validation process, documenting blockers and finding solutions to launch AI Factories at scale. Our results are spread across NVIDIA so we can succeed at scale.

Responsibilities

• Set up, adjust, and verify AI factory environments across multi-GPU and multi-node Linux clusters.
• Ensure configurations align with guidelines for NCCL, collectives, and distributed training frameworks.
• Own the execution of key AI/LLM benchmarks, including setup, orchestration, result collection, and analysis.
• Investigate and resolve issues when training jobs or benchmarks fail, hang, or underperform.
• Build and improve observability for AI factories (metrics, logs, traces, dashboards) to understand workload behavior and system health.
• Develop automation (Python, Shell) for running benchmarks, collecting results, and performing regression checks.
• Examine communication patterns and NCCL usage for AI/LLM workloads, concentrating on collectives such as AllReduce and AllToAll.
• Recommend changes to job configuration, parallelism strategies, and cluster settings to improve throughput, latency, and scaling efficiency.
• Work closely with hardware, software, networking, datacenter, and product teams to prepare AI factories for customer use.
• Contribute to documentation, guidelines, and readiness collateral that support internal collaborators and customer-facing teams.

Requirements

• Bachelor’s degree or equivalent experience in Computer Science, Mathematics, Engineering, Physics, or related field.
• More than 6+ years of experience managing Linux-based systems in HPC, distributed systems, or extensive AI/ML settings.
• Hands-on experience running AI/ML workloads on multi-GPU and/or multi-node clusters, with practical knowledge of NCCL.
• Solid grasp of collective communication patterns, particularly AllReduce and AllToAll, and how they are applied in contemporary ML/LLM training.
• Familiarity with LLM training and/or inference workflows using frameworks such as PyTorch or TensorFlow.
• Proficiency with Python and Shell/Bash for scripting, automation, and tooling.
• Experience with benchmarking (crafting, executing, and interpreting performance benchmarks).
• Comfortable working with observability data (metrics, logs, dashboards) to troubleshoot and optimize complex distributed workloads.
• Strong communication skills and the ability to work effectively with cross-functional teams.

Qualifications

• Experience with AI factory or large-scale AI infrastructure build, deployment, or operations.
• Background in HPC performance engineering, SRE, or systems performance analysis for GPU-accelerated environments.
• Familiarity with observability stacks (e.g., metrics/monitoring, logging, tracing systems) used for large distributed systems.
• Experience building automation and CI-style pipelines for running and validating benchmarks at scale.
• Demonstrated desire to use AI to solve practical problems, improve workflows, and guide data-driven decisions.

Skills

• Expertise in Linux-based systems management.
• Knowledge of NVIDIA's NCCL library and collective communication patterns.
• Experience with AI/ML frameworks like PyTorch or TensorFlow.
• Proficiency in Python and Shell scripting.
• Ability to develop and maintain automation scripts for benchmarking and testing.
• Understanding of observability and troubleshooting techniques for distributed systems.
• Excellent problem-solving and analytical skills.

Benefits

• Competitive base salary ranging from $148,000 to $235,750 based on location, experience, and market.
• Equity and comprehensive benefits package.

Pay

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

Schedule

This posting is for an existing vacancy. Applications for this job will be accepted at least until July 18, 2026.

Contact Information

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.