Within Perception, the Data Primary team builds and operates the data infrastructure that powers Waymo's perception foundation models. We design scalable pipelines that process petabytes of sensor data and allow everything from rare event mining to large-scale offline model deployment. Our work directly supports model training, evaluation, and production, ensuring that perception models have the high-quality, diverse data they need to perform safely. We collaborate across ML, Simulation, and Infrastructure teams to integrate data into the model lifecycle and help bring new capabilities to the Waymo Driver.

In this hybrid role, you will report to an engineering manager.

You will:

• Design and improve large-scale data pipelines that serve ML and research teams

• Deploy and maintain data flows for reliable, high-quality dataset delivery

• Apply ML techniques (e.g., embeddings, active learning) for data search and curation

• Build tools for scalable data mining and offboard inference

• Work to accelerate new model deployment across cities and platforms

You have:

• C++ programming skills (required), with Python experience

• 4+ years of experience with large-scale data systems (e.g., Spark, Beam, or Dataflow)

• Background in ML data engineering, data curation, or active learning

• Experience building and maintaining end-to-end ML data pipelines

• Collaboration skills with model, infra, and product teams

We prefer: