The Roadgraph team builds the intelligent platform and automated pipelines that create, validate, and scale the high-definition geo knowledge base powering the Waymo Driver. We combine applied machine learning, computer vision, statistical evaluation, and large-scale distributed systems to solve one of the most foundational and exciting challenges in autonomous driving.

High-definition mapping is a foundational pillar enabling the Waymo Driver to navigate safely, smoothly, and reliably. To rapidly expand commercial autonomous ride-hailing to new cities and continents, we must scale our automated mapping pipelines. This role sits at the center of that mission—building the applied ML models, evaluation engines, and large-scale data infrastructure that transform real-world sensor streams into the world's most precise and reliable spatial knowledge base.

We work closely with onboard engineers to solve problems in an end to end fashion. You will be working on all aspects of the modeling life cycle (labeling, training, evaluation, inference), put your models to work, and measure impact on the overall system.

You will:

• Evaluate and launch machine learning models that automatically generate map from raw data.
• Work with onboard teams to evolve Waymo’s mapping format to make it more automation friendly.
• Apply statistical analysis to validate large-scale changes.
• Build backend infrastructure for storing and processing many forms of map data.
• Scale our systems to support mapping the whole world.

You have:

• B.S. in Computer Science or a similar technical field, or equivalent practical experience.
• Hands-on experience with statistical analysis, experiment design, and quantitative evaluation of ML models or data pipelines.
• Experience building scalable data processing pipelines using distributed frameworks like Google Data Flow or Apache Beam.
• Demonstrated ability to take ownership of complex technical problems end-to-end and deliver measurable results in a collaborative team environment.
• A passion for good software engineering.

We prefer:

• Master’s or Ph.D. in Computer Science, Machine Learning, Robotics, Computer Vision, or a related quantitative field.
• Experience with high-performance computing, C++ optimization, and large-scale distributed systems architecture.
• Domain familiarity with autonomous vehicles, robotics, high-definition (HD) mapping or GIS/spatial databases.

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