Job description

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. Hardware Engineering is a diverse, innovative, and collaborative group of electrical, mechanical, reliability, software and vehicle engineers. We design, build, and perfect the products which are the eyes and ears of Waymo's autonomous driving technology, and integrate those products into vehicle platforms. We're seeking curious and talented teammates to keep us moving in the right direction. This role follows a hybrid work schedule and you will report to a Software Engineering Manager. You will: Develop algorithms to improve the accuracy and robustness of our core state estimation algorithm. Engineer and deploy robust, production-quality C++ software to fuse data from inertial, GNSS, and other advanced sensors into our algorithm for both new and existing vehicle platforms. Build and maintain tools, pipelines, and evaluation frameworks to rigorously assess positioning system performance across millions of miles of real-world driving data. Leverage Waymo's massive datasets to conduct large-scale analyses and optimizations, fine-tune sensor models, characterize system performance, identify root causes of failures, and establish performance guarantees. Collaborate closely within a multi-disciplinary team of engineers to solve complex technical challenges, contribute to a culture of high standards, and share your expertise with fellow team members. You have: MS, PhD or equivalent industry experience. Expertise in state estimation theory and application, including Kalman Filters, particle filters, factor graphs, and nonlinear optimization techniques. Deep understanding of inertial navigation principles, including sensor modeling, IMU error characterization, calibration, and multi-sensor fusion with GNSS and other aiding sensors. Strong C++ skills and ability to write high quality production level code. We prefer: Previous experience in the autonomous vehicle industry, particularly in inertial navigation, localization, perception, or sensor fusion. Experience with computer vision, visual inertial odometry, SLAM, ICP or other sensor modalities. Experience developing and using tools for large-scale data analysis and visualization (e.g., SQL, Python with libraries like NumPy, Pandas, Matplotlib). Familiarity with machine learning techniques applied to sensor fusion, sensor calibration, or positioning problems. 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 $204,000 — $259,000 USD

Requirements

Must-haves

This role follows a hybrid work schedule and you will report to a Software Engineering Manager.
Develop algorithms to improve the accuracy and robustness of our core state estimation algorithm.
Engineer and deploy robust, production-quality C++ software to fuse data from inertial, GNSS, and other advanced sensors into our algorithm for both new and existing vehicle platforms.
Build and maintain tools, pipelines, and evaluation frameworks to rigorously assess positioning system performance across millions of miles of real-world driving data.
Leverage Waymo's massive datasets to conduct large-scale analyses and optimizations, fine-tune sensor models, characterize system performance, identify root causes of failures, and establish performance guarantees.
Collaborate closely within a multi-disciplinary team of engineers to solve complex technical challenges, contribute to a culture of high standards, and share your expertise with fellow team members.
MS, PhD or equivalent industry experience.
Expertise in state estimation theory and application, including Kalman Filters, particle filters, factor graphs, and nonlinear optimization techniques.
Deep understanding of inertial navigation principles, including sensor modeling, IMU error characterization, calibration, and multi-sensor fusion with GNSS and other aiding sensors.
Strong C++ skills and ability to write high quality production level code.
Previous experience in the autonomous vehicle industry, particularly in inertial navigation, localization, perception, or sensor fusion.
Experience with computer vision, visual inertial odometry, SLAM, ICP or other sensor modalities.
Experience developing and using tools for large-scale data analysis and visualization (e.g., SQL, Python with libraries like NumPy, Pandas, Matplotlib).
Familiarity with machine learning techniques applied to sensor fusion, sensor calibration, or positioning problems.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlpythonmachine learning

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Vision