Staff Software Engineer - Simulation Realism

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.

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.

The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Our team is a diverse, and collaborative group of software engineers, machine learning (ML) engineers, and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. By applying machine learning, we model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions.

A key aspect of our simulation effort is the generation of foundational data that enables realistic simulation and trustworthy evaluations. This involves producing high-fidelity world representations from complex, large-scale multi-modal sensor datasets. We face significant challenges in ensuring the quality and accuracy of these signals, and in engineering robust, scalable systems for handling massive data volumes. This includes designing and implementing effective data lifecycle management strategies to maintain data integrity and accessibility.

In this hybrid role, you will report to a Sr Staff TLM.

You will:

• Design and develop scalable C++ and Python software systems for our data generation and management platform.


• Build and optimize data pipelines for processing, labeling, and curating large-scale multi-modal sensor data.


• Implement robust data lifecycle management, versioning, and storage solutions.


• Improve the performance, reliability, and scalability of the data platform.


• Collaborate with engineers and researchers to define and build data APIs and interfaces.


• Contribute to the long-term architecture of the simulation data ecosystem.

You have:

• BS or MS in Computer Engineering, Computer Science, or equivalent.


• 7+ years of experience in software development, focusing on backend or infrastructure.


• Strong coding and design skills in C++ and/or Python.


• Experience with large-scale data processing systems (e.g., Flume, Beam, Spark).


• Experience with databases, data warehousing, and production monitoring.


• Ability to solve open-ended technical and system design challenges.

We prefer:

• Experience building data platforms, data lakes, or ML feature stores.


• Familiarity with data management best practices for ML.


• Experience with large-scale multi-modal data.


• Experience developing user-facing APIs and interfaces.