Own the architecture and operation of large-scale autonomous-driving datasets, from multimodal vehicle-data ingestion through curation, quality monitoring, labeling, versioning, and ML training delivery. Design schemas, storage, query, distributed pipelines, observability, and reproducible dataset splits. Lead data-quality, drift, anomaly, auto-labeling, human-review, and closed-loop workflows, including trajectory preparation for imitation learning and offline reinforcement learning. Provide staff-level technical leadership across autonomy, annotation, storage, governance, and model teams.