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 ML Ops team, part of Waymo ML Platform team, builds tools and infrastructure to realize the ML flywheel at Waymo. This includes building automation and orchestration solutions to make complex ML workflows manageable and reliable. This team also partners closely with the modeling team to realize solutions to speed up developer velocity.

We're looking for a software engineer to join the team to build and maintain the critical data and ML pipelines that powers ML development at Waymo.

In this hybrid role, you will report to a Technical Lead Manager, Staff Software Engineer.

You will:

• Implement new features in Waymo's data flywheel to scalably process ML data
• Develop robust ML workflows to continuously and automatically train, evaluate, and deploy models for Waymo's onboard and offboard applications
• Support the reliable operation of ML pipelines at scale
• Collaborate with ML modeling teams in understanding their workflows & design automation solutions that solve their problems

You have:

• Bachelor's degree in Computer Science, Engineering, or related field, and 2+ years equivalent experience
• Experience with distributed systems principles and experience building distributed systems for production environments.
• Solid Python or C++ skills
• Experience monitoring, debugging, and troubleshooting complex distributed systems
• Experience communicating updates and resolutions to customers and other partners

We prefer:

• Experience with ML Ops principles and best practices

#LI-Hybrid

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.