Staff Tech Lead, ML Data Infrastructure and Inference Platform

Waymo - Mountain View, CA, USA - original posting ->
Status
Open
Remote policy
Hybrid
Employment type
Not stated
Salary
251,000-310,000 USD / year
Categories
Sys Intel and Machine Lrng (SQT)
Tech
cpphybridmlstaff
Source
waymo
First observed
2026-09-23 18:46 UTC
Last seen
2026-09-23 18:46 UTC
Source claims posted
2026-09-23 16:38 UTC
Consecutive misses
0 of 3

What the posting says

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 Data Infrastructure and Inference Platform team owns the Data as well as the Data infrastructure for all ML Flywheels at Waymo. We do this via a planet scale centralized feature store for all ML training and evaluation, the feature extraction framework as well the inference platform for generating the data via bulk and online inferences. The objective of the team is to deliver data necessary for all our onboard as well Foundation Models to make the ML Flywheel successful and in turn lead to the successful scaling of Waymo. The team is highly collaborative and closely works with all modeling teams within Waymo.

You will:

As a Tech Lead you’ll build, lead and contribute to Waymo’s ML data infrastructure platform to enable planet scale ML Flywheel for all ML models at Waymo via data store and data infra ecosystem.

Work closely with teams across Waymo both onboard & offboard Foundation models, to understand the data infra needs, data distributions, data quality, data value, freshness and onboard these flywheels onto our planet scale data store and ensure the seamless adoption and guide the development of our infra components.

You will closely lead, mentor and guide a team of engineers to build and onboard teams to the infrastructure efficiently.

The team has a large surface area and scope in terms of impact, cross team collaboration and direct interaction with ML models at Waymo.

You have:

6+ years of professional experience in the field of software engineering

Experience tech leading projects with high cross team collaboration

Experience tech leading a team of engineers on complex projects

Experience in programming C++

Experience with building highly scalable distributed system

Experience with ML Data and ML Flywheels

We prefer:

Passionate about Data and building ML infra & tools

Experience Tech leading projects, cross functional projects

Experience with handling large datasets in the order of exabytes

Experience building machine learning infrastructure and model hosting / inference infrastructure

Experience with production services with high QPS.

#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.

Salary Range

$251,000—$310,000 USD

Quality

Completeness: 100%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #953634 2026-09-23 18:46 UTC
    Published