Nvidia Technical Marketing Engineer - World Models Physical AI 

United States, California 

532162048

What You'll Be Doing:

• Develop and Deliver Technical Content: Create and present high-impact, performance benchmark based technical marketing materials to drive enterprise and developer audiences towards adoption of NVIDIA.

• Core Content Development: Build whitepapers, technical guides and blogs, videos, demos and solution briefs driving through NVIDIA sales and marketing teams to our partners and customers.

• Cross-Functional Teamwork: Collaborate with product, research, and engineering teams to deeply understand features, roadmaps, and differentiators, enabling the creation and delivery of advanced technical materials on large multimodal models, multi-task learning, video networks, generative models, imitation learning, and semi-supervised learning for technical sales teams.

• Customer and Community Engagement: Serve as a domain expert on World Models to capture feedback, respond to technical queries, and exhibit world models development and integration workflows and examples.

• Enable Sales & Partners: Build training and enablement materials for developer relations teams, partners, and customers.

• Advance Thought Leadership: Support industry-firsts, developer success stories, analyst briefings, and speaking engagements.

What we need to see:

• A BS Degree in Computer Science or Engineering related field with or equivalent experience in a technical marketing role (or equivalent experience)

• 8+ years of experience in technical marketing, developer enablement, or a related technical field with a focus on foundation models use and evangelism.

• Skilled at translating sophisticated AI concepts into clear, engaging messaging for both technical and business audiences.

• Strong communication and collaborator leadership skills in matrixed, multi-functional environments.

• Comfortable with Python and tools like Hugging Face, PyTorch, Docker, or similar for model evaluation, inference, and code-level artifact review (config files, training checkpoints).

• Develop and improve technical content for corporate and software developer communities previously.

• Experience running generative AI models - LLMs, diffusion models, or VLMs / VLAs - along with a working understanding of their inputs, outputs, failure modes, and performance bottlenecks.

Ways to Stand Out From The Crowd:

• Hands-on experience developing and delivering workshops or certification programs at industry events.

• Proficiency in software development standard methodologies, such as integrating AI agents into workflows.

• Deep understanding of foundation models and GPU-accelerated deployments.

• Strong understanding of AI licensing, model/data provenance, and traceability systems is a plus.

• Technical proficiency with NVIDIA technologies (Omniverse, Cosmos, CUDA, TensorRT, Triton Inference Server, etc.).