Responsibilities

• Design and post-train foundation models (LLMs, VLMs, VLAs and DiTs) for real world applications across industries with a bias towards AV.
• 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 platforms.
• Core Content Development: Build whitepapers, technical guides and blogs, videos, demos and solution briefs driving through NVIDIA sales and marketing teams to our AV partners and customers.
• Work with teams in research, software, and products to bring world models from idea to deployment.
• Serve as a domain expert in the area of World Models for autonomous vehicles. Capture feedback and respond to technical queries. Demonstrate development and integration workflows and examples.
• Enable Sales & Partners: Use training and enablement materials for developer relations teams, partners, and customers.
• Prototype and iterate rapidly on experiments across powerful AI domains, including agentic systems, reinforcement learning, reasoning, and video generation in partnership with customer / partner teams.
• Advance Thought Leadership: Support industry-firsts, developer success stories, analyst briefings, and speaking engagements.

Requirements

• A BS Degree in Computer Science or Engineering related field or equivalent experience accompanied by comparable experience in a technical marketing role
• 8+ years of experience in technical marketing, developer enablement, or a related technical field with a focus on foundation models in AV 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 AV AI models - LLMs, diffusion models, or VLMs / VLAs - along with a working understanding of their inputs, outputs, failure modes, and performance bottlenecks.

Preferred

• 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.).