Enterprise Platform Technical Marketing Engineer Intern - Summer 2027

NVIDIA•Santa Clara, CA

1d•$20 - $71

About The Position

As an Enterprise Platform TME intern, you will help accelerate adoption of NVIDIA Enterprise solutions by building the workflows, demos, and technical content that show partners and customers what GPU-accelerated platforms make possible. You will stand up AI and agentic AI workflows end to end and then explain them clearly to engineering audiences and at public events, developing the technical marketing assets that bring them to life — product and technology demonstrations, videos, playbooks, and targeted content. A core part of the role is translating Enterprise Platform capabilities into real-world use cases across Manufacturing, AECO, and Media & Entertainment. Working closely with key OEM partners and internal teams, you will help define the demos that showcase GPU-enabled enterprise platforms, produce the technical collateral that supports them, and enable customers to develop AI locally on the systems they already trust. Position includes owning a summer project: a "hero demo" showcasing an end-to-end GPU-accelerated workflow; Pitch the demo concept directly, driving ownership of the idea from the start; A follow-on project may be assigned if the hero demo is completed early and to a high standard.

Requirements

Pursuing a BS or MS in Computer Science, Computer Engineering, or a related technical field (graduating December 2027 or later)
Programming experience in Python
Working knowledge of Linux and Windows, including command-line tooling and system configuration
Hands-on experience with an AI or machine learning framework such as PyTorch, TensorFlow, or Hugging Face
Experience documenting a technical workflow and presenting it to a technical audience

Nice To Haves

Experience with large language models, retrieval-augmented generation (RAG) pipelines, or agentic AI frameworks such as LangChain, LlamaIndex, or NVIDIA NIM
Familiarity with CUDA, GPU acceleration concepts, or NVIDIA developer software development kits such as TensorRT, RAPIDS, or Omniverse
Working knowledge of containers and environment management (Docker, Conda, WSL), Git, and C/C++ or shell scripting
Hands-on PC or workstation hardware experience, including component installation, system bring-up, driver troubleshooting, and benchmarking
Projects you can demo: a GitHub portfolio, hackathon builds, research prototypes, technical blogs, or demo videos

Responsibilities

Building AI and agentic AI workflows end to end on NVIDIA platforms, including hardware bring-up and troubleshooting
Creating technical marketing assets such as product demonstrations, videos, playbooks, and one-pagers
Translating enterprise platform capabilities into real-world use cases across manufacturing, architecture and construction, and media and entertainment
Defining and testing demos alongside original equipment manufacturer (OEM) partners and internal teams, and organizing a shared demo library
Owning a summer "hero demo" project: an end-to-end GPU-accelerated workflow that you pitch and then build