World Model Lead

About the institute

Role

Technical leadership

• Define architecture covering multimodal ingestion, mixed continuous/discrete representations, hierarchical generative modeling, an enhanced LLM backbone, and diffusion-based predictors.
• Ground generative loss in real observations and use simulation for reinforcement-learning-based agent training.
• Set performance, safety, and evaluation benchmarks and drive continuous improvement.

Projects and collaboration

• Oversee project planning, resourcing, and timelines; manage research engineers and scientists.
• Integrate world-model outputs with agent, reasoning, and deployment teams for robotics, multi-turn dialogue, and autonomous systems.
• Work with academic and industry collaborators and report project status, risks, and insights to stakeholders.
• Champion reproducibility, documentation, and knowledge sharing.

Required qualifications

• Ph.D. or M.S. with 8+ years in AI research or engineering specializing in world modeling, simulation, or generative modeling.
• Track record building large-scale simulators or predictive models for complex environments.
• Deep expertise in transformer-based LLMs, diffusion models, and hierarchical latent representations.
• Hands-on reinforcement-learning framework experience, including policy learning and planning with latent dynamics.
• Leadership skills in project management, cross-site coordination, and team mentorship.

Preferred qualifications

• Experience leading multi-location technical teams in fast-paced R&D settings.
• Published contributions to world-model architectures or simulation benchmarks.
• Experience moving research prototypes into production systems.