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Waymo

Staff Software Engineer, Machine Learning, Planner Selection

Waymo

Published 11 May 2026
Mountain View, CA, USA
238K - 302K USD Annual
Full Time

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Role Highlights

Languages used

C++

Key skills

Machine Learning
Computer Science
Interpretability
PhD
Robotics

Tools, Libraries and Frameworks

Description

The individual in this role will investigate driving behavior issues by analyzing logs to determine root causes. They will work to improve the performance of machine learning models within the planner system. The position involves developing foundational frameworks to advance the capabilities of the autonomous driving technology. Furthermore, the role focuses on expanding the impact of models while maintaining interpretability and behavioral guarantees. The contributor will address complex driving situations encountered in the long tail of autonomous operations.

Required Qualifications and Skills

Candidates must possess a Master's or PhD degree in Computer Science, Machine Learning, or a related discipline. Proficiency in C++ or Python is required, along with practical experience implementing machine learning models in production systems. It is preferred that applicants have eight years of software engineering experience in complex systems, as well as background in autonomous vehicles or robotics.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

Waymo

Description

Waymo is an autonomous driving technology company that began as the Google Self-Driving Car Project in 2009. With a mission to enhance mobility and safety, Waymo has developed the Waymo Driver, powering their fully autonomous ride-hailing and local delivery services. To date, Waymo has achieved over 20 million miles of autonomous driving on public roads across 25 US cities and 20 billion miles of simulation testing. The company emphasizes mission-driven innovation and a collaborative culture, aiming to improve access to mobility while prioritizing safety and community impact.

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