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Data & AnalyticsHybrid

Senior / Staff Machine Learning Engineer - Perception Attributes

Zoox · Hybrid

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Last seen by MeritLog September 10, 2026Source: LeverSource version: lever-postings-v1

MeritLog read this listing from Zoox's Lever job board and last checked it on September 10, 2026.

Source: the employer's Lever job board. Open the original listing for current details.

Job details

Work model
Hybrid
Salary
$254,000 - $350,000
Location
Foster City, CA

Hiring context

How this role compares at Zoox

Zoox has 245 live roles in MeritLog’s catalog across 11 job families, and 46 of them are in data & analytics. 230 of those listings publish a pay range, a disclosure rate of 94%.

This role's posted range of $254,000 - $350,000 sits above 89% of the 223 other Zoox roles quoted over the same currency and period.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

Job description

As a machine learning engineer within the Attributes team in the Perception department, you will take ownership of developing and enhancing sophisticated behavioral models for various road users, including vehicles, pedestrians, and cyclists. Your work will focus on creating and maintaining robust perception attribute models that generate critical signals for our autonomous driving stack. These signals are essential inputs that enable our Prediction and Planning teams to make intelligent, safe driving decisions for our autonomous vehicles.  The Attributes team is fundamental to Zoox's autonomous driving capabilities. The models you develop will serve as the foundation for how our vehicles understand and interact with other road users, directly contributing to the safety and effectiveness of our autonomous driving system. By creating reliable and accurate behavioral models, you enable Zoox's vehicles to make smart, safe decisions in complex urban environments, bringing us closer to our goal of revolutionizing urban mobility.

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