Senior Machine Learning Engineer, Growth

📋 Description

• Own the feature layer between the Growth DB and the models. Work with data engineering on schema
• Build point-in-time correct training data, so a retrain sees each day as it was and does not leak
• Take models data science has trained and put them into production: validate against the offline
• Lead training automation: scheduled retrains, a model registry, and validation before a new model
• Monitor models in production: feature drift, score distribution shifts, and model versus random arm
• Be data science's day-to-day engineering counterpart, so feature and modeling questions do not

🎯 Requirements

• Experience at roughly building production ML systems: feature pipelines, training data generation
• Strong SQL and Python, plus large-scale data processing (Flume, Beam, Spark or similar).
• Designed feature schemas or worked on a feature store, and understands point-in-time correctness
• Productionized and owned the lifecycle of an existing offline model
• Worked with data scientists and can turn a loose feature request into a spec.

🎁 Benefits

• Waymo's discretionary annual bonus program
• Equity incentive plan
• Generous Company benefits program
• Opportunity to work for an autonomous driving technology company