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NVIDIA
NVIDIA
H1B Visa SponsorArtificial IntelligenceHealthcareManufacturing
NVIDIA develops accelerated computing and artificial intelligence technologies used across gaming, data centers, cloud computing, healthcare, manufacturing, automotive, and robotics. Its work spans graphics processing units, AI platforms, simulation, and industry-focused solutions, including NVIDIA Omniverse for collaborative 3D workflows, NVIDIA DRIVE for autonomous vehicle development, and NVIDIA Clara for healthcare applications. The company brings together large technical teams working on the infrastructure and software that support advanced computing, simulation, and AI-driven analytics.
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NVIDIA Senior AI and HPC Infrastructure Solutions Architect, Texas Remote

Design GPU clusters and accelerated infrastructure for NVIDIA energy-sector customers as a senior AI solutions architect. Advise on deployments spanning AI, high-performance computing, cloud, and edge environments.

USUnited StatesTXTexas
$184,000 – $356,500 / year
RemoteFull-timeSeniorEnglish RequiredSolutions Engineer
CloudDistributed SystemsDockerKubernetesNode.js

Description

  • Work with energy customers, software vendors, and account teams on discovery, architecture reviews, technical evaluations, proofs of concept, benchmarks, demos, and production deployment advice.
  • Guide the design, deployment, and optimization of accelerated AI infrastructure, including large GPU clusters, AI factories, and edge systems.
  • Help design infrastructure across compute, networking, storage, containers, observability, security, power, and data center operations.
  • Promote monitoring, telemetry, and management tools that improve cluster utilization, reliability, performance, and workload visibility.
  • Share findings and help others learn through examples, white papers, blogs, and collaborative customer problem-solving.
  • Create reference architectures, deployment and sizing guides, benchmark reports, technical playbooks, demos, and white papers.
  • Build strategic relationships with key customers and industry-focused solution partners.
  • Work primarily with colleagues and customers through virtual collaboration tools.
  • Travel of up to 20% may be required for customer meetings.

Requirements

  • Bachelor’s, master’s, or doctoral degree in computer science, electrical or computer engineering, physics, another engineering discipline, or a related field; equivalent experience is also accepted.
  • At least eight years of hands-on work in AI infrastructure, accelerated computing, distributed systems, cloud infrastructure, high-performance computing, or machine learning platforms.
  • Demonstrated ability to design, deploy, and operate accelerated computing infrastructure at scale.
  • Detailed understanding of orchestration, scheduling, automation, and continuous integration and deployment pipelines for AI clusters.
  • Knowledge of data center networking, including InfiniBand, Ethernet, RDMA, network configuration, and performance tuning.
  • Familiarity with distributed training, inference serving, model deployment, storage performance, and cluster reliability needs.
  • Working knowledge of at least one energy sector and its operational and IT environments.
  • Experience designing AI factories, large GPU clusters, multi-node training environments, or production inference platforms.
  • Experience deploying large-scale infrastructure workflows for LLM training, fine-tuning, retrieval-augmented generation, and inference.
  • Experience measuring cluster performance with MLPerf, HPL, or workload-specific tests.
  • Application and systems-level knowledge of OpenMPI, NCCL, distributed training frameworks, and GPU communication patterns.
  • Comfort using Docker or other containers and Kubernetes.
  • Strong presentation, communication, problem-solving, documentation, and collaboration abilities.
  • Able to structure complex problems and work independently to deliver results on ambiguous projects with multiple stakeholders.

Benefits

  • Equity compensation
  • Employee benefits

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