Senior Solutions Architect, AI and HPC Infrastructure

🕒 6 days ago

🤠 Texas – Remote

🤠 Texas – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 1%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

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

• Partner with energy-sector customers, ISVs, and account teams on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and production deployment guidance • Advise on the design, build-out, and optimization of accelerated AI infrastructure, including large-scale GPU clusters, AI factories, and edge deployments • Support infrastructure design across compute, networking, storage, containers, observability, security, power, and data center operations • Drive adoption of systems monitoring, telemetry, and management tools to improve cluster utilization, reliability, performance, and workload insight • Document learnings and teach others through samples, whitepapers, blogs, and customer problem-solving • Build reference architectures, deployment guides, sizing guidance, benchmark reports, technical playbooks, demos, and whitepapers • Partner strategically with flagship customers and industry-specific solution partners • Collaborate primarily through virtual tools • Travel up to 20% for customer meetings may be required

🎯 Requirements

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, other Engineering, or related field (or equivalent experience) • 8+ years of hands-on experience in AI infrastructure, accelerated computing, distributed systems, cloud infrastructure, high-performance computing, or machine learning platforms • Strong experience designing, deploying, and operating accelerated computing infrastructure at scale • In-depth knowledge of AI cluster orchestration, scheduling, automation, and CI/CD deployment pipelines • Understanding of data center networking technologies such as InfiniBand, Ethernet, RDMA, network configuration, and performance tuning • Familiarity with distributed training, inference serving, model deployment, storage performance, and cluster reliability requirements • Working knowledge of one or more energy sectors and their operational and IT environments • Experience architecting AI factories, large GPU clusters, multi-node training environments, or production inference platforms • Experience deploying LLM training, fine-tuning, RAG, and inference workflows on large-scale AI infrastructure • Experience evaluating cluster performance using MLPerf, HPL, or workload-specific performance tests • Applications and systems-level knowledge of OpenMPI, NCCL, distributed training frameworks, and GPU communication patterns • Comfortable with Docker/Containers and Kubernetes • Excellent presentation, communication, problem-solving, documentation, and collaboration skills • Strong problem structuring and self-direction to drive ambiguous, multi-stakeholder projects to results

🏖️ Benefits

• Equity • Benefits