Staff Technical Lead Manager, Scenes, Onboard Map Expansion at Waymo (Mountain View, CA / San Francisco, CA)
Waymo· Mountain View, CA / San Francisco, CA· $251k–$310k·
Role details
Job description
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.
The Onboard Map Expansion team develops tech and API towards building driving logic that is robust to map correctness and availability. Waymo is rapidly scaling its driving to new cities and service areas -- each new service area comes with certain nuances that are unique to them (unique map configurations, different road rules, etiquette, etc.). Our team builds the tech and tools to rapidly discover, iterate, and mitigate these behaviors while also scaling the performance of the car in a data-driven way.
This is an opportunity to shape how Waymo solves the scaled-driving problem in new service areas. There are several open questions both technically and from a product point of view, and this role offers a front row seat to how Waymo scales its driving!
In this role, you will report to an Engineering Manager.
You will
- Working closely with leads and TLMs in the org to design and implement horizontal solutions to solve behavioral driving issues in new cities
- Build quantitative evaluation techniques to drive data driven development
- Work closely with partners in Mapping, Product, and the rest of the Onboard stack
You have:
- PhD, Masters or Bachelors degree in Computer Science, Machine Learning, Robotics, or a related field
- Experience manipulating and analyzing large datasets
- Experience with working and solving design problems that cut across multiple components. High quality API design with an eye towards eval and data driven techniques.
We prefer:
- Experience in the autonomous driving domain, including areas like motion planning or perception
- Proficiency in SQL
- Proficiency in C++
- Evaluation experience, contributing to scalable eval workflows and building metrics for ML models
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Salary Range $251,000—$310,000 USD
Why work at Waymo
- Impact: Work on technology that directly saves lives (1.4M traffic deaths globally each year) and reshapes the future of transportation.
- Culture: Waymo describes itself as a place for “ambitious thinkers and relentless problem solvers” with a deep respect for getting every detail right. Values include safety, innovation, and responsibility.
- Teams: Opportunities across Software Engineering, Hardware Engineering, AI Foundations, Product & Design, Operations & Supply Chain, Safety, Policy, and General & Administrative roles.
- Internships: Strong early-career program with internships for Bachelors, Masters, MBA, and PhD candidates, often leading to full-time offers.
- Hiring process: Transparent and structured. Includes an initial recruiter screen, 1-2 phone/video interviews, and a virtual onsite (up to 5 interviews). Emphasizes problem-solving, collaboration, and real-time thinking. AI tools are not permitted during technical assessments to ensure fair evaluation.
- Remote/hybrid policy: The careers page lists both on-site and remote roles, with most engineering and operations roles based in Mountain View, San Francisco, or other US locations.
- Benefits: Top-notch benefits, unique learning opportunities, thoughtful community engagement, and meaningful gatherings. Specific perks are not detailed publicly but are described as comprehensive.