Senior Solutions Architect, First Time Deployment Validation

🔥 0 minutes ago

🏄 California, Texas, +2 more states – Remote

🏄 California – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote ☕ Washington – Remote

💵 $148k - $235.8k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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.

🏖️ Benefits

• equity • benefits