Tech Stack
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.
AI @ 3
Agentic AI @ 3
CUDA @ 2
Docker @ 3
GPU @ 2
Git @ 3
GitHub @ 3
LLM
LangChain @ 3
Linux @ 3
Machine Learning @ 3
Marketing
PyTorch @ 3
Python @ 3
RAG @ 3
Software Development @ 2
TensorFlow @ 3
TensorRT @ 2
- 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 is seeking an Enterprise Platform Technical Marketing Engineer Intern to help accelerate adoption of NVIDIA Enterprise solutions. The role involves building workflows, demos, and technical content that demonstrate the capabilities of GPU-accelerated platforms to partners, customers, and engineering audiences.
The intern will stand up AI and agentic AI workflows end to end, explain them clearly, and develop technical marketing assets including product and technology demonstrations, videos, playbooks, and targeted content. The role focuses on translating Enterprise Platform capabilities into real-world use cases across manufacturing, architecture, engineering, construction, media, and entertainment.
The position includes ownership of a summer project: a "hero demo" showcasing an end-to-end GPU-accelerated workflow. The intern will pitch the demo concept and drive 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.
Responsibilities
- Build AI and agentic AI workflows end to end on NVIDIA platforms, including hardware bring-up and troubleshooting.
- Create technical marketing assets such as product demonstrations, videos, playbooks, and one-pagers.
- Translate enterprise platform capabilities into real-world use cases across manufacturing, architecture and construction, and media and entertainment.
- Define and test demos alongside original equipment manufacturer (OEM) partners and internal teams.
- Organize a shared demo library.
- Own a summer "hero demo" project involving an end-to-end GPU-accelerated workflow that you pitch and build.
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.
Preferred Qualifications
- 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 tools including Docker, Conda, and WSL.
- Experience with Git and C/C++ or shell scripting.
- Hands-on PC or workstation hardware experience, including component installation, system bring-up, driver troubleshooting, and benchmarking.
- Demonstrable projects such as a GitHub portfolio, hackathon builds, research prototypes, technical blogs, or demo videos.
Benefits
Interns are eligible for NVIDIA intern benefits.
Applications for this job will be accepted at least until October 17, 2026. NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.