Teams at Zoox

Develop deep learning models using imitation and reinforcement learning to generate autonomous vehicle trajectories. Build production ML pipelines, metrics, and error-analysis tools; evaluate driving plans for safety, progress, and comfort; and collaborate with Planning, Perception, Simulation, and Systems Engineering teams to improve autonomous driving in complex urban environments.

Perform system safety analyses for autonomous vehicle sensing and perception systems. Define safety requirements, metrics, and fail-operational architectures for camera, lidar, radar, sensor fusion, and machine learning subsystems. Lead cross-functional safety projects, apply ISO 26262 and SOTIF methods, guide sensor architecture decisions, analyze field and simulation data, and support safety arguments for public-road deployment. The role also involves data analysis, system-level tradeoffs, and using AI/LLM tools to improve efficiency.

Leads architecture, optimization, scaling, and ownership of Zoox’s enterprise and AI data platform. Builds self-healing pipelines, governance frameworks, data quality and observability systems, secure access controls, lifecycle policies, and automated CI/CD deployment infrastructure. Optimizes Databricks and AWS EMR performance and costs while enabling low-latency, AI-ready data foundations. The role also drives enterprise security, compliance, schema evolution, and developer velocity, with opportunities to apply GenAI, Terraform, and EKS.