About the job
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
Waymo is rapidly scaling its driving technology to new cities and geographies. A continual focus on operational efficiency, compliance, and safety is critical to this mission. The Driver Refinement & Validation organization builds the technology and tools to rapidly discover, iterate, and mitigate complex vehicle behaviors while scaling performance in a data-driven way.
The PUDOs (Pick-up/Drop-off) team is directly responsible for perfecting how our fully autonomous car executes pullovers—improving key driving scenarios like passenger pick-ups and drop-offs, parking, and deliveries. As we expand, our goal is to build the advanced signals and software necessary to seamlessly scale the Waymo Driver's performance across these critical real-world touchpoints in every new market.
In this role, you will report to a Technical Lead Manager.
Responsibilities
Work closely with Technical Leads and Technical Lead Managers in the org to design and implement horizontal solutions to solve behavioral driving across PUDOs (pick up & drop off)
Build quantitative evaluation techniques of on-road performance to drive data-driven development
Work closely with partners across Product and the Onboard stack
Provide mentorship for junior engineers on the team
Develop foundational frameworks that help advancement of the Waymo Driver's capabilities
Directly contribute to solving some of the most challenging driving situations in the long tail
Qualifications
Minimum
PhD, Masters, or Bachelors degree in Computer Science, Machine Learning, Robotics
8+ years of Software Engineering experience in complex systems
Evaluation experience, contributing to scalable eval workflows and building metrics for ML models and analyzing large datasets
High quality API design with an eye towards evaluation and data-driven techniques
Experience with working and solving design problems that span multiple components
Ability to collaborate within and across teams
Two or more years of management experience
Preferred
AV or Robotics experience
Experience with Machine Learning models in production systems
Coding proficiency in C++, Python, and SQL