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.
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
5+ years of experience with large-scale data systems (e.g., Spark, Beam, or Dataflow), or PhD and 3+ years
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:
Experience with vector search (Faiss, ScaNN) or RAG systems
Knowledge of ML infra for foundation model training and evaluation
Familiarity with data-centric AI (few-shot, fine-tuning, pre-training)
Background in autonomous systems or robotics
MS/PhD or published work in ML or large-scale data systems
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.
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