Machine Learning Engineer, Fleet Monitoring & Response

You will:

• 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.

You have:

• BS degree in Computer Science or equivalent practical experience.
• 5+ 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.

We prefer:

• MS in Computer Science, or equivalent practical experience.
• Experience building and deploying ML / Optimization models into production environments.
• Experience developing ML data pipelines and ML workflow automation code on top of a mature ML infra. 
• Experience working at another Ride hailing or Marketplace company.
• Coursework background in ML and Optimization.