Senior Software Engineer - ML/ Fraud Prevention
Senior engineer on Waymo's fraud prevention team in Warsaw, building ML models that score rider risk in real time to stop payment fraud and vandalism. Day-to-day: training and shipping production models, low-latency feature pipelines over payment/trip/device events, and real-time model serving on critical trip and payment paths. Stack mentions Python, Java, Kotlin, C++, Go and SQL.
- Compensation
- Not disclosed
- Location
- Warsaw, Poland
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 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
- 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
Full 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.
You will:
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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.
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Engineer and maintain high-throughput, low-latency feature pipelines over payment, trip, device, and identity events, ensuring consistency between offline training and online serving.
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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.
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Design and implement safe, graduated enforcement mechanisms with full audit trails, reversibility, and support for rider appeals.
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Partner cross-functionally with Product, Finance, and Safety to balance revenue protection, rider trust, and compliance as Waymo scales to new markets.
You have:
-
Bachelor's degree in Computer Science, Mathematics, Statistics, or equivalent practical experience.
-
8+ 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.
We prefer:
-
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.