Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Marketing @ 3
Security @ 3
Cumulus Linux @ 2
Kubernetes @ 3
Linux @ 2
MLOps @ 3
Networking @ 3
PKI @ 3
Cloud Computing @ 3
GPU @ 2
AI @ 3
Slurm @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA Cloud Accelerator team develops full stack AI solutions for data centers. This role is a Technical Marketing Engineer focused on AI Infrastructure, Cloud, and Data Center Management software. You will help cloud and ecosystem partners deploy and use NVIDIA technology, demonstrate full-stack integrations, and assist users configuring physical systems, networking, and multi-tenant software to support AI solutions.
Responsibilities
- Illustrate methods for deploying and managing infrastructure software: build automation, demos, and reference examples showing how to deploy and manage NVIDIA's infrastructure software components.
- Build and drive integrations across the stack: collaborate with Technical Marketing Engineering, Product, Engineering, and Field teams to demonstrate how layers of data center hardware, infrastructure management software, AI platforms, and AI use cases work together.
- Enable the field with technical assets: publish reference architectures, deployment guides, and code examples to help field teams and partners integrate NVIDIA technologies; engage in customer-facing engagements alongside Solution Architects.
- Engage and support the developer community: advocate for NVIDIA technology within the cloud-native ecosystem to encourage adoption of NVIDIA's infrastructure software.
Requirements
- 8+ years data center and infrastructure expertise, including configuring and deploying compute nodes, storage, and networking.
- Experience with cloud-native deployments and managing containerized deployments and Kubernetes clusters.
- Experience with infrastructure-as-code and developing automation for managing and deploying infrastructure software and cloud-native technologies.
- Background in cloud computing and security, including cloud AI/ML platforms and multi-tenant architecture.
- Strong cross-functional collaboration skills and ability to work alongside multiple teams and customers.
- Technical ability to contribute to engineering developments, defend technical opinions, and make prioritized decisions independently.
- BS or MS in engineering, computer science, or another technical field (or equivalent experience).
Ways to stand out
- Experience with more than one cloud service provider.
- Familiarity with NVIDIA DPUs and DOCA and/or switch operating systems like Cumulus Linux and MLNX-OS.
- Experience managing tenant and/or physical/virtual environment security and secure key management / certificate lifecycle operations (PKI concepts, OCSP, CRLs, enrollment protocols, key rotation, revocation).
- Familiarity with NVIDIA technologies and products including Base Command Manager, DGX Cloud, Run:ai, GPU Operator, Network Operator.
- Experience with Slurm and/or Kubernetes-based MLOps platforms.
Compensation & Benefits
- The base salary will be determined based on location, experience, and comparable pay. The posting states the base salary range is 160,000 USD - 253,000 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5.
- You will also be eligible for equity and benefits.
Additional information
- Applications for this job will be accepted at least until March 10, 2026. This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and provides a comprehensive benefits package. For benefits details see www.nvidiabenefits.com.