Senior Technical Marketing Engineer - DSX AI Infrastructure Software

Details

NVIDIA DSX brings together facilities infrastructure, hardware, software, simulation, and partner technologies to build and run efficient AI factories. The Senior Technical Marketing Engineer will show and educate the AI factory ecosystem how to bring up and operate the entire stack, ranging from facilities and multi-node GPU infrastructure to provisioning, networking, storage, cluster orchestration, security, observability, and workload enablement.

Responsibilities

• Stand up and validate complete DSX-aligned software stacks on multi-node GPU systems, documenting dependencies, configuration order, validation steps, and operational handoffs.
• Turn working deployments into technical content, including reference architectures, quick-starts, installation and upgrade guides, troubleshooting runbooks, code examples, blogs, whitepapers, and demo videos.
• Build reusable examples and automation using APIs, Python or shell scripting, infrastructure as code, containers, Kubernetes, Slurm, Helm, GitOps, and CI/CD where appropriate.
• Build demos, labs, and training covering AI factory operations, including deployment, tenant setup, upgrades, monitoring, scheduling, fault isolation, remediation, capacity management, and security.
• Demonstrate how data center hardware, infrastructure and cluster management software, orchestration, AI platforms, and workloads operate as one system.
• Test pre-release software with representative training and inference workloads, identify interoperability and resiliency issues, and provide feedback to Product and Engineering.
• Support solution architects, field teams, cloud and OEM partners, ISVs, and system integrators through repeatable assets, train-the-trainer sessions, live demos, and direct support.
• Collaborate with open-source and cloud-native communities to demonstrate integration approaches, address documentation and usability shortcomings, and assist partners in expanding the DSX software stack.
• Identify recurring customer, partner, field, and developer problems; set content priorities, recommend product improvements, and track operational outcomes.
• Present work in customer briefings, partner workshops, industry events, webinars, and internal training. Some travel is required.

Requirements

• BS or MS in Computer Science, Computer Engineering, Electrical Engineering, another 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 a related role.
• Hands-on experience deploying and operating Linux-based data center, cloud, HPC, or AI infrastructure, including multi-node GPU systems and production operational practices.
• Strong working knowledge of Kubernetes and/or Slurm, including containers, operators, Helm charts, cluster lifecycle, and workload scheduling.
• Experience in several infrastructure domains, such as bare-metal provisioning, firmware and drivers, compute, Ethernet or InfiniBand networking, 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, such as deployment guides, documentation, reference architectures, code repositories, demos, workshops, blog posts, conference talks, or training.
• Excellent written, verbal, and visual communication skills, with the 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.

Preferred Qualifications

• Experience with NVIDIA DSX, DGX systems, DGX Cloud, NVIDIA AI Enterprise, BlueField DPUs, DOCA, or related NVIDIA infrastructure software.
• Experience operating large GPU clusters and diagnosing distributed performance, networking, storage, scheduling, or hardware-health issues.
• Experience with AI training and inference workloads on accelerated infrastructure.
• Experience connecting infrastructure software to facilities or operational technology systems, including power, cooling, and building management systems.
• Active participation in cloud-native, HPC, infrastructure automation, or open-source communities.

Benefits

NVIDIA offers competitive salaries, equity, and a comprehensive benefits package.

The base salary range is USD 160,000–253,000 for Level 4 and USD 200,000–322,000 for Level 5. Applications will be accepted at least until August 30, 2026.