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 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. In this hybrid role, you will report to an Engineering Manager 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 5+ 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: 8+ 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 $251,000 — $310,000 USD

Requirements

Must-haves

In this hybrid role, you will report to an Engineering Manager
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.
BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area, or equivalent work experience
5+ 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
8+ years of experience building productionized ML models
Experience in reinforcement learning, transfer learning, or learning.
Experience with large scale data and models

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlpython

Platform: greenhouse
Effort: quick