Machine Learning Engineer, Depot Automation

Waymo
Mountain View, US
Hybrid

Who this role is best for

Best suited to mid-level machine learning engineers with robotics experience working in autonomous vehicle operations and depot automation.

Best fit for

  • Engineers with hands-on experience in industrial robotics and large-scale ML deployment.
    — “3+ years of experience with robotics, preferably industrial robotics
  • Candidates who can bridge ML research with operational needs in autonomous fleets.
    — “Interface closely with operations teams to translate real-world needs into robust, working solutions
  • Researchers with PhDs applying reinforcement learning to industrial automation challenges.
    — “A PhD in Machine Learning, Robotics, or a related technical field

Things to consider

  • Hybrid work arrangement requires presence in Mountain View office.
    — “This role follows a hybrid work schedule
  • Must integrate ML solutions at production scale, not just research prototypes.
    — “Integrate ML models in production at scale

How to stand out

  • Highlight specific examples of deploying RL solutions in industrial settings.
    — “Expertise in reinforcement learning and its applications to real-world problems
  • Demonstrate collaborations with operations teams to implement technical solutions.
    — “Background in collaborating with internal and external research partners
  • Showcase experience with foundation models beyond traditional ML approaches.
    — “Leverage foundation models, reinforcement learning, and simulation
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Mid Level

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Drive operational efficiency for autonomous fleet
  • Contribute to complex depot operations
  • Leverage foundation models and reinforcement learning
Typical background
3+ years experience in training and evaluating large machine learning models

Skills & requirements

Required

Machine LearningRoboticsReinforcement LearningSimulationProduction Integration

Preferred

Phd In Machine Learning, Robotics, Or A Related Technical FieldExperience With Applying Machine Learning Techniques To Large-scale Industrial Problems

Stack & domain

Machine LearningRoboticsReinforcement LearningSimulationAutonomous DrivingDepot Automation

About the role

Original posting from Waymo

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.

This role is at the intersection of robotics and machine learning, driving the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet. You will lead efforts to generalize complex depot operations—such as exterior cleaning, sensor calibration, and maintenance checks—using advanced robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to translate real-world needs into robust, working solutions.

This role follows a hybrid work schedule and reports to a Director, Hardware and Sensors.

 

You will:

Drive the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet

Contribute to accomplishing complex depot operations using advanced robotics

Focus on complex depot operations, such as charging, interior cleaning, vehicle inspection, and routine vehicle maintenance tasks

Leverage foundation models, reinforcement learning, and simulation

Integrate ML models in production at scale

Interface closely with operations teams to translate real-world needs into robust, working solutions

 

You have:

3+ years of experience in training and evaluating large machine learning models

3+ years of experience with robotics, preferably industrial robotics 

Expertise in reinforcement learning and its applications to real-world problems

 

We prefer:

A PhD in Machine Learning, Robotics, or a related technical field or equivalent experience 

Experience with applying machine learning techniques to large-scale industrial problems is a plus

Background in collaborating with internal and external research partners on applying ML to large-scale industry scale problems

 

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$175,000—$215,000 USD

Source: Waymo careers

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