Lead and oversee data programs that power the development and enhancement of autonomous vehicle systems through machine learning and AI models. This role combines technical leadership, program management, and deep understanding of data requirements for autonomous systems.



Key job responsibilities
Architect and execute the data strategy for autonomous vehicle training programs, including data collection, curation, labeling, and validation workflows
Lead cross-functional teams spanning data operations, ML engineering, perception teams, and vehicle systems
Define and implement data quality standards, annotation specifications, and validation processes for diverse sensor data (LiDAR, radar, camera, etc.)
Manage relationships with data annotation vendors and establish KPIs for data quality and throughput
Drive development of scalable data pipeline infrastructure and tools for efficient data processing
Create and track program metrics, timelines, and deliverables across multiple workstreams
Identify edge cases and scenarios needed to improve model performance and safety
Partner with legal and privacy teams to ensure compliance with data handling regulations

About the team
We build and operate autonomous systems for last-mile delivery. Our team combines robotics, AI, and logistics expertise to create reliable delivery solutions that work in real urban environments. Our engineers and researchers focus on computer vision, autonomous systems, and operations, working to solve technical challenges in urban mobility. We partner with city planners, logistics companies, and communities to deploy delivery robots that integrate into existing infrastructure. Our work aims to make city deliveries faster, cheaper, and cleaner through automation.