- Robot type
- Autonomous Vehicle
- Location
- San FranciscoCaliforniaUSA
- Job type
- Artificial Intelligence
- Posted
- May 18, 2026
- Salary
- $213,000–$263,000 a year
Senior Machine Learning Engineer, Fleet Monitoring & Response
Job description
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.
Job responsibilities
- 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…
- 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…
- Partner with Product Data Scientists to productionize, evaluate, and scale experimental models, translating notebooks and prototype algorithms into production-grade systems.
Job requirements
- BS degree in Computer Science or equivalent practical experience.
- 6+ years of experience programming in backend coding languages such as Java or C++.
- 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.
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