Senior Software Engineer, Inertial Navigation

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.