Senior Software Engineer - ML/ Fraud Prevention

Waymo

Warsaw, Poland

Who this role is best for

A natural match if you have experience in fraud prevention and building distributed backend systems.

Best fit for

Individuals with 5+ years of experience in distributed backend systems and a focus on adversarial domains
— “5+ years of software engineering experience building distributed backend systems or production ML systems”
Professionals who have implemented low-latency model serving infrastructure for critical business logic
— “Build and operate the real-time model serving infrastructure integrated into the critical trip creation and payment authorization paths”

Things to consider

The role requires maintaining data consistency between offline training and real-time inference
— “Engineer and maintain high-throughput, low-latency feature pipelines over payment, trip, device, and identity events”
Geographic constraints may apply for US-based remote roles, though not explicitly for Warsaw
— “Please speak with your recruiter about your preferred location for remote work when you begin the interview process”

How to stand out

Emphasize experience with real-time model serving and fraud detection systems in your resume and interviews
— “Train, evaluate, and ship production machine learning models to score rider risk in real time”
Showcase your ability to design graduated enforcement mechanisms with audit trails and reversibility
— “Design and implement safe, graduated enforcement mechanisms with full audit trails, reversibility, and support for rider appeals”
Demonstrate hands-on ML deployment experience, especially in low-latency environments
— “Experience serving models or critical business logic in low-latency, high-availability production environments”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

deploying machine learning models in production
building and maintaining feature pipelines
operating real-time model serving infrastructure

Typical background

software engineeringmachine learningdistributed systems

Skills & requirements

Required

Machine LearningDistributed SystemsFeature PipelinesReal-time Model ServingData Modeling

Preferred

Fraud PreventionAnomaly DetectionGraph/entity-clustering TechniquesRules Engines

Stack & domain

PythonJavaKotlinC++GoFraud PreventionRisk ManagementTrust & SafetyPayments

About the role

Original posting from Waymo

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:
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.
You 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.
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.
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.
Disclosure for WA Based & Remote Roles:
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
Health, dental, vision, life, disability insuranceRetirement Benefits: 401(k) with company matchPaid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employmentSick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year
US Remote Only: Please note that Waymo may not be able to employ remotely in all US locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process.

Source: Waymo careers