Job Description

Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

The Perception team at Waymo builds technology that powers the Waymo Driver. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We conduct research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling ML practitioners like you to develop multi-modal models and techniques at scale.

Our mission is to build a stable foundation for a high-level Perception pipeline and the overall self-driving system. We act as the crucial interface between Waymo's hardware teams and the rest of the self-driving engineering organization, defining sensor requirements, providing critical feedback to hardware teams, and abstracting away system complexities.

In this hybrid role, you will report to the Director of Engineering.

You will:

• Provide technical leadership on the efficacy and efficiency of the core hardware abstraction layer and sensor integration.


• Collaborate closely with hardware and Perception teams to design, set the roadmap, and implement the foundational system that underpins Perception ML software stack.


• Work on and design end-to-end data flow and processing pipelines from sensors to the perception outputs, ensuring high performance and reliability.


• Solve large-scale data challenges related to sensor integration, calibration, and data consistency across diverse hardware configurations.


• Drive and accelerate collaborations between Perception, hardware teams at Waymo, and other Alphabet collaborators.

You have:

• Master’s degree or PhD in Computer Science, Engineering, or a related technical field


• 8+ years of experience in ML related software development


• 6+ years of experience in production systems involving sensor integration, data processing, or real-time perception.


• 4+ years of experience in a technical leadership role leading technical teams and setting technical directions


• 3+ years of experience with hardware-software interaction, sensor integration, or general robotics systems.


• Passion to drive engineering excellence and efficient model development through flywheel automation, while having direct technical experience in model quality development to achieve business goals

We prefer:

• Experience in robotics, autonomous systems, or related automotive industries.


• Experience with various sensor modalities (e.g., LiDAR, radar, cameras) and their unique challenges.


• Experience in model techniques and infrastructure


• Familiarity with vision-based models and their development challenges

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

$281,000—$356,000 USD

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