Senior Software Engineer - ML/ Fraud Prevention

You will:

• Train, evaluate, and ship production machine learning models to score rider risk in real time, directly protecting revenue from payment fraud and reducing vehicle vandalism.

• Engineer and maintain high-throughput, low-latency feature pipelines over payment, trip, device, and identity events, ensuring consistency between offline training and online serving.

• Build and operate the real-time model serving infrastructure integrated into the critical trip creation and payment authorization paths under strict latency and availability budgets.

• Design and implement safe, graduated enforcement mechanisms with full audit trails, reversibility, and support for rider appeals.

• Partner cross-functionally with Product, Finance, and Safety to balance revenue protection, rider trust, and compliance as Waymo scales to new markets.

• Bachelor's degree in Computer Science, Mathematics, Statistics, or equivalent practical experience.

• 5+ years of software engineering experience building distributed backend systems or production ML systems (Python, Java, Kotlin, C++, Go, or similar).

• Hands-on experience training, evaluating, and deploying machine learning models to production.

• Experience serving models or critical business logic in low-latency, high-availability production environments.

• Strong fundamentals in data modeling, and SQL analytics.

Nice to have

• Experience in fraud prevention, risk management, trust & safety, payments, or another adversarial domain where attackers actively adapt.

• Experience with graph/entity-clustering techniques, rules engines, and anomaly detection alongside traditional ML.

• Proven track record building feature/data pipelines and maintaining consistency between training data and real-time inference.

• Experience serving models or critical business logic in low-latency, high-availability production environments.