Senior Machine Learning Engineer, Simulation

Posted 10 Hours Ago
Be an Early Applicant
2 Locations
In-Office
204K-259K Annually
Senior level
Automotive
The Role
Develop production-grade machine learning models and infrastructure to evaluate autonomous vehicle behavior in simulation and real-world environments. Collaborate across teams to deploy state-of-the-art ML systems, improve model quality, and support large-scale data and simulation workflows.
Summary Generated by Built In

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 Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack.

You will:

  • Report into the TLM for the Learned Metrics Team
  • Develop ML models that assess our autonomous vehicle's behavior.
  • Develop ML infrastructure to support performant models.
  • Collaborate across teams to bring state-of-the-art to production.

You have:

  • BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area, or equivalent work experience
  • 2+ years of experience building productionized ML models
  • Code and design skills: comfort building production systems (Python / C++)
  • Background in applied Deep Learning
  • A track record in improving model quality

We prefer:

  • 4+ years of experience building productionized ML models
  • Experience in reinforcement learning, transfer learning, or learning.
  • Experience with large scale data and 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
$204,000—$259,000 USD

Skills Required

  • Bachelor's degree in Computer Science, Robotics, Statistics, Physics, Mathematics, another quantitative field, or equivalent work experience
  • 2+ years of experience building productionized machine learning models
  • Programming and system design skills using Python and C++
  • Background in applied deep learning
  • Track record of improving model quality
  • 4+ years of experience building productionized machine learning models
  • Experience with reinforcement learning, transfer learning, or learning
  • Experience with large-scale data and models

Waymo Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Waymo and has not been reviewed or approved by Waymo.

  • Fair & Transparent Compensation — Pay is considered strong for full‑time technical roles, aligning with top‑tier AV/Big Tech benchmarks. Employer materials also emphasize competitive pay with eligibility for bonuses and equity as part of total rewards.
  • Healthcare Strength — Coverage spans medical, dental, vision, mental‑health resources, onsite wellness centers, and counseling, with specialized programs such as menopause and transgender medical advocacy. Dependents are included, indicating depth across core health needs.
  • Parental & Family Support — Offerings include fertility and family‑forming assistance, parental and baby‑bonding leave, caregiver and elder‑care support, and backup childcare. These programs are positioned to support families through multiple life stages.

Waymo Insights

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The Company
HQ: Mountain View, CA
2,359 Employees
Year Founded: 2009

What We Do

Waymo is an autonomous driving technology company with a mission to make it safe and easy for people and things to move around. With the Waymo Driver, we can improve the world’s mobility while saving thousands of lives. Waymo reaches out to candidates from official channels only (e.g. directly from @waymo.com email addresses, or through our recruiters or sourcers who are noted as such on LinkedIn). We do not contact candidates about career opportunities through instant messaging apps like Telegram, email addresses from domains other than waymo.com (such as Gmail addresses), direct messages on Twitter, Facebook, and Instagram, or text messages. Visit waymo.com to check out our official job listings.

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