Machine Learning Engineer - Fraud Risk

The role

You will architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral analysis. You will develop end-to-end ML pipelines and design low-latency, real-time decision systems.

What you will do

• Architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral analysis
• Develop and maintain end-to-end ML pipelines
• Design and implement low-latency, real-time decision systems
• Own ML infrastructure, including model versioning, automated retraining, and safe deployment strategies
• Build robust monitoring and alerting for model performance, latency, data quality, and drift
• Lead experimentation on model explainability, drift detection, and adversarial robustness
• Develop tooling and processes to improve the ML development lifecycle
• Partner with platform teams to meet strict SLAs
• Collaborate with engineers, data scientists and compliance teams

Required qualifications

• 5+ years of experience building ML systems in production
• At least 2+ years in fraud, risk, or anomaly detection domains
• A degree in Computer Science, Engineering, Statistics, Applied Math, or a related technical field
• Proven track record designing and maintaining ML models at scale
• Advanced proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Strong understanding of supervised/unsupervised learning, anomaly detection, and statistical modeling
• Ability to work autonomously, manage ambiguity, and collaborate closely with data scientists
• Experience developing, validating, and productionalizing predictive real-time and offline fraud detection models using supervised and unsupervised ML techniques
• Experience collaborating with cross-functional teams to prioritize, scope, and deploy MLI solutions at scale

Nice to have

• Domain expertise in banking, payments, or transaction monitoring
• Experience with graph-based or network-level fraud detection techniques
• A graduate degree in Computer Science, Engineering, Statistics, Applied Math, or a related technical field
• Experience fine-tuning or adapting generative AI / large language models for pattern generation or synthetic data augmentation
• Knowledge of model governance, bias mitigation, and regulatory compliance in fraud contexts

Benefits

• Unlimited time off (10 days minimum required)
• Flexible working
• Stipend to set up a home workspace
• For US Rainmakers, 95% of health, dental, and vision plan costs and 90% for dependents
• 100% company-subsidized life insurance plan
• 401(k) with a 4% company match
• Equity option plan
• Monthly stipend for eligible health and wellness spending
• In-office meals via DoorDash credit
• Team and company offsites, both domestic and international

About the company

Rain is the global stablecoin payments platform for enterprises, neobanks, platforms, developers, and AI agents. It delivers secure, scalable infrastructure that makes money move freely and instantly around the world.