The opportunity
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…
What you'll do
Design, scale, and optimize Waymo's real-time Fleet Monitoring and event: response engine to support expansion to global operating locations.
Develop and deploy spatial-temporal anomaly detection models (e.g., S2-cell: statistical regressions) and leverage Multimodal Foundation Models (Gemini/VLMs) to detect, triage, and automatically respond to off-nominal operations.
Build and standardize the ML infrastructure for fleet monitoring models,: including automated training/inference pipelines, low-latency spatial data stores (e.g., in-memory S2 grids), and continuous model drift monitoring.
Partner with Product Data Scientists to productionize, evaluate, and scale: experimental models, translating notebooks and prototype algorithms into production-grade systems.
BS degree in Computer Science or equivalent practical experience.
+ years of experience programming in backend coding languages such as Java or C++.
What they're looking for
- Experience in building backend platforms supporting multiple product use-cases/services.
- Prior Machine Learning Engineering experience in Python using mature ML: frameworks such as TensorFlow, PyTorch or Keras.
- MS in Computer Science, or equivalent practical experience.
- Experience building and deploying ML / Optimization models into production environments.
