Develop behavioral and motion-planning algorithms that help autonomous vehicles maintain trip progress and uptime through system failures, integrating solutions across the driving stack and validating their performance.
Zoox jobs
Zoox develops purpose-built autonomous vehicles for robotaxi and ride-hailing services.
154 open roles at Zoox
Lead machine learning development for autonomous-vehicle perception, creating algorithms and multimodal models for scene understanding, sensor data, simulation, and validation while shaping technical direction across teams.
Software Engineer - Learned Trajectory Machine Learning Engineer
Develop deep learning models that generate autonomous vehicle trajectories, evaluate plans for safety, progress, and comfort, and improve driving systems through metrics, analysis, and cross-team collaboration.
Senior / Staff Software Engineer - Learned Trajectory Machine Learning Engineer
Develop deep learning models that generate autonomous vehicle driving trajectories, assess plans for safety, progress, and comfort, and improve behavior through machine learning tools and cross-team collaboration.
Leads strategic sourcing and supplier partnerships for vehicle components and operations infrastructure, shaping procurement roadmaps, negotiating contracts, managing supplier performance, and identifying cost efficiencies.
Leads the Product Software organization and ride-hailing platform, overseeing engineering teams building the customer app, fleet backend, operational tools, and in-vehicle experience while scaling a customer-focused product.
Develop behavioral and motion-planning algorithms that help autonomous vehicles maintain trip progress and uptime through system failures, integrating scalable solutions across the driving stack.
Leads and scales executive recruiting, advising senior leaders on talent strategy while personally driving Director+ searches, building a research function, and managing a small recruiting team.
Lead analysis of fleet and simulation data, develop and evaluate machine learning methods, validate model performance for safety and reliability, and mentor data scientists and engineers advancing autonomous driving systems.
Develop and test real-time motion-planning algorithms that improve autonomous vehicle driving behavior, using simulation, closed-course testing, and on-road reviews to expand safe performance in complex situations.
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