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2024-05-07 Waymo

Machine Learning Technical Lead and Manager

London, England, United Kingdom

Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

The Simulator team builds state of the art simulations of realistic environments for the testing and training of the Waymo driver. We use machine learning extensively to model the real world, including but not limited to, realistic agents (vehicles, pedestrians, cyclists, motorcyclists etc.),  roads, traffic control systems, weather etc. To increase the fidelity and steerability of the simulations, we employ large foundation models, trained on our massive datasets that allow us to quickly setup and rollout various scenarios to subject our driver to.


We are planning to set up a team in London UK to work closely with the teams in MTV and Oxford to build these foundation models out and to integrate them into various evaluation and training products. We are seeking a Tech Lead Manager to build and lead this team.


In this leadership role, you'll:

  • Build a world class research engineering team to advance the state of the art of ultra realistic AV simulations using foundation models
  • Collaborate with Waymo Oxford to use large models to improve sim realism
  • Design experiments that push the frontiers of AV simulations
  • Develop metrics that measure the realism of simulated worlds
  • Train and evaluate large models and integrate them into the simulator and its downstream applications
  • Hire outstanding research engineers from diverse backgrounds
  • Build a high performing, collaborative research engineering team that takes research ideas and productionizes them


Preferred qualifications

  • Strong background and experience in applied Deep Learning
  • Experience in managing research engineering teams
  • Strong coding and design skills
  • Experience in solving complex production problems using state of the art ML techniques
  • Experience in taking research to production
  • Expertise in Data Analysis or Data Science
  • Team building skills including hiring and mentoring
  • Experience in AV a plus


The expected base salary range for this full-time position 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.  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
£175,000£189,000 GBP
We appreciate your interest in Waymo. Waymo is an equal employment opportunity employer, committed to maintaining a supportive and inclusive workplace for all employees. Waymo does not discriminate against, and prohibits harassment of, any applicant or employee based on race, color, sex, sexual orientation, gender identity, religion, national origin, age, disability, military status, genetic information or any other basis protected by applicable law. Waymo will also consider for employment qualified applicants with criminal records in accordance with applicable law. Waymo is committed to ensuring equal opportunity for qualified individuals with disabilities. If you are an individual with a disability and require an accommodation to participate in the application or interview process, please let the recruiting team know or email (This email address is intended to be used only for requesting accommodations as part of the application process. Other inquiries will not receive a response.)

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