The DGX Cloud team at NVIDIA builds groundbreaking AI solutions, systems and cloud offerings. This role will be a key person in the technical team helping our customers make the most of their DGX Cloud solutions. This individual will work across the TME team to build DGX Cloud solutions and publish public-facing content, that will help customers use the platform and be successful in building AI solutions.
What you’ll be doing:
-
As a Technical Marketing Engineer, you will focus on accelerating the adoption of NVIDIA DGX Cloud by our customers by creating public-facing content via code examples, documentation, presentations, webinars, blog posts, etc. focusing on the development, optimization and integration of key cloud infrastructure and platform technologies in the application and development of AI solutions.
-
This role will work with the other members of the technical marketing team, our engineering, product management, product marketing teams, our partners, and our customers to both develop new integrated solutions and examples showcasing DGX Cloud and its associated technologies, as well as create core product assets and content, such as user guides, technical overviews, etc. for new releases and versions of the product.
-
Working with the field, you will leverage these assets and examples to educate and train both our internal teams as well as customers about DGX Cloud and its capabilities.
-
Public speaking at industry events, internal and external trainings and presentations, giving live demos, and webcasts will be a key part of the job.
-
Some travel is required to support events.
What we need to see:
-
Knowledge in creating customer-facing assets, product documentation, content such as demos, technical presentations, tutorials, webinars, demo videos, etc. Links to example contributions are greatly appreciated.
-
Experience developing AI workflows and solutions on CSP AI platforms, including examples such as Amazon SageMaker, Azure AI Studio, Google VertexAI. Experience with more than one cloud is preferred.
-
Experience configuring and managing CSP technologies for storage, compute, networking, security, such as S3 and GCS object storage, VPCs and private links/connectivity, compute clusters, etc. Experience deploying such components for use with AI platforms and solutions is preferred.
-
Background in scripting automation and management CSP infrastructure platforms and services
-
Experience in scripting automation and deployment of AI workflows, workloads, and MLOps/LLMOps pipelines.
-
Proven ability to work with and create complex multi-faceted solutions spanning multiple layers of the AI software stack and ecosystem.
-
Ability to balance multiple projects and responsibilities and prioritize under tight deadlines.
-
Ability to delve into engineering developments and technical details of products, and strong ability to defend opinions with both business and technical partners within the organization.
-
Bachelors in computer science or engineering or equivalent experience.
-
12+ years of applicable experience.
Ways to stand out from the crowd:
-
Familiarity with AI/Deep Learning frameworks and workloads
-
Experience with Slurm / Kubernetes / MLOps platforms
-
Background with cloud AI platforms and solutions and CSP technologies
-
Experience with more than one cloud service provider
-
Examples of published work you authored or created
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and dedicated people in the world working for us. If you're creative and autonomous, we want to hear from you!
The base salary range is 200,000 USD - 310,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
 (1).png)
