Drimva

NVIDIA

Technical Marketing Engineer, World Models - AV Physical AI

$148K–$288K

US, CA, Santa Clara · Full-time · Posted Sep 22, 2026

Experience
8+ years; technical marketing, developer enablement, or a related technical field.
Education
BS in Computer Science or Engineering-related field, or equivalent experience.

About the job

Develop and promote NVIDIA world models for autonomous vehicles through model prototyping, technical content, developer enablement, and customer engagement.

What you'll do

  • Design and post-train foundation models, and prototype AI experiments for real-world applications, especially autonomous vehicles.
  • Create and present technical materials, demonstrations, training, and enablement resources for developers, customers, partners, and sales teams.
  • Collaborate across research, software, product, and partner teams to support world-model deployment and answer technical questions.

What they ask for

  • BS in Computer Science or an engineering-related field, or equivalent experience, accompanied by comparable experience in a technical marketing role.
  • 8+ years in technical marketing, developer enablement, or a related technical field focused on foundation models in AV use and evangelism.
  • Experience with generative AV models (LLMs, diffusion models, VLMs, or VLAs) and their inputs, outputs, failure modes, and performance bottlenecks.
  • Comfort with Python and tools such as Hugging Face, PyTorch, and Docker or similar for model evaluation, inference, and code-level artifact review.

Nice to have

  • Experience developing and delivering workshops or certification programs at industry events.
  • Knowledge of AI licensing, model/data provenance, and traceability systems; technical proficiency with NVIDIA technologies is also noted as a plus.

Pay

148,000 USD - 235,750 USD base salary (Level 4); 184,000 USD - 287,500 USD base salary (Level 5)

Tools

Python, Hugging Face, PyTorch, Docker, Omniverse, Cosmos, CUDA, TensorRT

AI focus

Design and post-train foundation models for autonomous vehicles; prototype agentic systems, reinforcement learning, reasoning, and video generation; evaluate and demonstrate AI model workflows and deployments.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)