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Senior Technical Marketing Engineer - DSX AI Infrastructure Software

NVIDIA· Engineer, Technical Marketing
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Santa Clara, CA, Hybrid (Remote (CA))$160k - $322kFull-timePosted 1mo ago

About the role

Senior Technical Marketing Engineer to educate and enable the AI factory ecosystem, from facilities and multi-node GPU infrastructure to provisioning, networking, storage, cluster orchestration, security, observability, and workload enablement within NVIDIA DSX.

Responsibilities

  • Stand up and validate complete DSX-aligned software stacks on multi-node GPU systems. Capture dependencies, configuration order, validation steps, and operational handoffs.
  • Turn working deployments into technical content: reference architectures, quick-starts, installation and upgrade guides, troubleshooting runbooks, code examples, blogs, whitepapers, and demo videos.
  • Build reusable examples and automation with APIs, Python or shell scripting, infrastructure-as-code, containers, Kubernetes, Slurm, Helm, GitOps or equivalent, and CI/CD where applicable.
  • Build demos, labs, and training addressing deployment, tenant setup, upgrades, monitoring, scheduling, fault isolation, remediation, capacity management, and security.
  • Show how stack layers fit together; collaborate with TME, Product, Engineering, and Marketing to demonstrate end-to-end operation.
  • Test pre-release software with representative workloads; provide actionable feedback to Product and Engineering.
  • Help solution architects, field teams, cloud/OEM partners, ISVs, and system integrators use the stack via assets, train-the-trainer sessions, live demos, and direct support.
  • Collaborate with open-source and cloud-native communities for integration approaches and usability improvements; assist partners in expanding DSX stack.
  • Capture customer/partner field signals to set content priorities and influence product improvements; track deployment time and operational success impact.
  • Present work in customer briefings, partner workshops, industry events, webinars, and internal training; some travel may be required.

Qualifications

  • BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related technical field, or equivalent experience.
  • 8+ years of experience in infrastructure engineering, systems engineering, solutions architecture, software engineering, technical marketing engineering, site reliability engineering, or related role.
  • Hands-on experience deploying and operating Linux-based data center, cloud, HPC, or AI infrastructure, including multi-node GPU systems and production operations.
  • Strong working knowledge of Kubernetes and/or Slurm, including containers, operators, Helm charts, cluster lifecycle, and workload scheduling.
  • Experience in core infrastructure domains such as bare-metal provisioning, firmware/drivers, compute, networking (Ethernet/InfiniBand), storage, identity/multi-tenancy, secrets or certificate management, telemetry, observability, and fleet health.
  • Ability to automate deployments and operations through scripting, APIs, configuration management, infrastructure-as-code, Git-based workflows, and CI/CD.
  • Examples of technical work for practitioner audiences (deployment guides, documentation, reference architectures, code repositories, demos, workshops, blog posts, talks, or training); links to contributions encouraged.
  • Excellent written, verbal, and visual communication skills; ability to explain complex systems and defend technical recommendations to business and technical partners.
  • Ability to balance multiple projects, prioritize under tight deadlines, and collaborate across Engineering, Product, Field, Marketing, and partner teams.

Skills

Required:Linux system administrationKubernetesAutomation / ScriptingDocumentation & content creation
Nice to have:Slurm

Benefits

  • Competitive salaries
  • Comprehensive benefits package
  • Equity eligibility
Last updated Oct 23, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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