Waymo

Waymo

Posted via Greenhouse

Tech Lead Manager, Foundation Models

Posted Aug 5, 2026

Role at a glance

Salary
$298K – $368K/yr
Location
Mountain View, California, United States Kirkland, Washington, United States
Work arrangement
Hybrid
Employment
Full-time

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Role Summary

AI-generated

The role leads the AI Foundations team at Waymo, which develops machine learning solutions for autonomous driving and foundation models supporting offboard and onboard Waymo Driver applications. The position reports to a Research Director and works with cross-functional teams across Waymo, including simulation, planner, semantics, and ML infrastructure.

What You'll Do

  • Lead and manage a team to build large-scale foundation models
  • Set the technical direction for the team and develop execution strategies
  • Align individual efforts with the overall strategies
  • Develop collaborative relationships with cross-functional teams across Waymo
  • Establish an inclusive culture for the team
  • Enable research innovations and deliver impactful results

Generated from the employer's posting. Verify important details before applying.

View full posting

Qualifications

Technical experience working with LLMs / VLMs or world models

Required

  • 2+ years of experience managing medium-size teams
  • Track record in developing team culture and growing people
  • 6+ years experience in deep learning research or applied research
  • Technical experience working with LLMs / VLMs or world models

Preferred

  • Strong background in foundation model related domains, such as pretraining, mid-training, post-training, Transformer modeling, model...
  • Experience working with productionizing deep learning models

Original job description

Content provided by the employer

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 mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

This role follows a hybrid work schedule and reports to a Research Director.

 

You will:

  • Lead and manage a team to build large-scale foundation models, powering many offboard and onboard applications for the Waymo Driver
  • Set the technical direction for the team, develop the execution strategies, and align individual efforts with the overall strategies
  • Develop a collaborative relationship with cross-functional teams across Waymo, including simulation, planner, semantics, and ML infrastructure
  • Establish an inclusive culture for the team, enabling research innovations and delivering impactful results

 

You have:

  • 2+ years of experience managing medium-size teams
  • Track record in developing team culture and growing people
  • 6+ years experience in deep learning research or applied research
  • Technical experience working with LLMs / VLMs or world models

 

We prefer:

  • Strong background in foundation model  related domains, such as pretraining, mid-training, post-training, Transformer modeling, model scaling, self-supervised learning.
  • Experience working with productionizing deep learning models

 

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

 

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
$298,000$368,000 USD
Waymo

About the company

Waymo

Large Enterprise

Waymo is a leading autonomous driving technology company, originally a part of Google's parent company Alphabet Inc. Established in 2009, Waymo focuses on developing self-driving cars and innovative transportation solutions designed to enhance mobility and safety on the roads. By employing advanced artificial intelligence and machine learning algorithms, the company aims to revolutionize personal and shared transportation, making it more accessible and efficient. Waymo's efforts contribute significantly to the future of autonomous vehicles and the ongoing shift towards smart transportation systems.