Responsibilities

• Serve as a trusted technical advisor for developers and partner engineering teams adopting Cosmos 3 across synthetic data generation and world-model workflows.
• Drive global adoption of Cosmos world foundation models with strategic partners, AI labs, and members of the NVIDIA Cosmos Coalition, from exploration to deployment.
• Build and maintain deep expertise in NVIDIA’s Physical AI stack, with a focus on world foundation models, post-training of WFMs, and video/action data curation.
• Track emerging trends in world models, video generation, and physical-AI reasoning to identify new opportunities for the Cosmos platform.
• Champion robotic ecosystem partners internally, providing feedback to NVIDIA’s Cosmos product and research teams to influence future roadmaps.
• Support product launches and marketing activities for events — including GTC, CVPR, CoRL, and ICRA — using ecosystem partner success stories.
• Accelerate critical partner workloads using NVIDIA’s core models, frameworks, and libraries.

Requirements

• 8+ years of overall professional experience with Vision and Perception algorithms, Robotics, or AI deployment.
• Master’s or PhD degree in Computer Science, Engineering, or a related technical field — or equivalent experience.
• Strong foundation in deep learning algorithms, including hands-on experience with LLMs, VLMs, multimodal generative models, and World Foundation Models.
• Working knowledge of Physical AI data workflows: large-scale video curation, captioning/annotation, domain randomization, and sim-to-real augmentation.
• Excellent interpersonal skills with the ability to distill complex technical concepts for diverse technical and non-technical audiences, from engineers to executives, and to structure and implement complex technical engagements.

Preferred

• Direct experience with NVIDIA Cosmos models (Predict, Transfer, Reason, or Cosmos 3).
• Hands-on experience deploying LLMs, VLMs, diffusion models, or WFMs at scale in real-world applications, especially for robotics or autonomous vehicles.
• Experience with NVIDIA tools and libraries in robotics (CUDA-X, Isaac Sim, Isaac Lab, OpenUSD, Omniverse).
• Contributions to open-source generative-model or robot-learning projects, or published research in world models, video generation, or embodied AI.
• Established network across AI labs, robotics companies, or AV programs building on world foundation models and proven success growing developer ecosystems through technical enablement and open-model community programs.