Lead development of map-grounded world foundation models and generative scenario synthesis for AVs. Own end-to-end ML lifecycle, bridge generative models with classical simulators, define synthetic data quality and validation frameworks, run POCs with partners, and enable sim-to-real strategies to improve perception and planning.

Lead strategy and execution for generative and multimodal vision systems, from research to production. Design model architectures, adaptation, evaluation, and deployment pipelines; improve realism, controllability, robustness, and temporal consistency; benchmark and guide model selection; mentor scientists and coordinate cross-functional engineering to ship production-ready AI capabilities.