Rain · 3 weeks ago
Machine Learning Engineer - Fraud Risk
New York, NY
Full-time
Hybrid
Senior Level
$187K/yr - $259K/yr
5+ years expRain is a company that makes the next generation of payments possible across the globe, focusing on stablecoin infrastructure. The Machine Learning Engineer will architect and build scalable ML systems for fraud detection and develop end-to-end ML pipelines while collaborating with various teams to ensure effective fraud risk management.
BlockchainCryptocurrencyDecentralized Finance (DeFi)FinTechWeb3
Responsibilities
Architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral analysis
Develop and maintain end-to-end ML pipelines: data ingestion, feature engineering, model training, deployment, and continuous monitoring
Design and implement low-latency, real-time decision systems partnering with fraud risk data scientists, integrating with transaction or behavioral data streams
Own ML infrastructure, including model versioning, automated retraining, and safe deployment strategies (e.g., shadow, rollback)
Build robust monitoring and alerting for model performance, latency, data quality, and drift
Lead experimentation on model explainability, drift detection, and adversarial robustness for fraud prevention use cases
Develop tooling and processes to improve the effectiveness and speed of the ML development lifecycle
Partner with platform teams to meet strict SLAs for availability, latency, and accuracy
Collaborate closely with talented engineer, data scientist and compliance teams across Rain
Work in a fast-paced environment on a rapidly growing product suite
Solve complex problems at the intersection of ML systems, data, and reliability
Qualification
Required
5+ years of experience building ML systems in production; at least 2+ 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 to translate analytical models into robust fraud prevention systems
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
Preferred
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 (in partnership with data science)
Knowledge of model governance, bias mitigation, and regulatory compliance in fraud contexts
Benefits
Unlimited time off
Flexible working
Easy to access benefits
Retirement goals
Equity plan
Rain Cards
Health and Wellness
Team summits
Company
Rain
Rain is a fintech company that builds stablecoin-powered payment infrastructure, allowing businesses and individuals to use tokenized money.
51-200 employees
H1B Sponsorship
Rain has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (2)
2023 (1)
2022 (1)
2021 (1)
Funding
Current Stage
Growth StageTotal Funding
$332.5MKey Investors
ICONIQ CapitalSapphire VenturesNorwest
2026-01-09Series C· $250M
2025-08-28Series B· $58M
2025-03-24Series A· $24.5M
Leadership Team
Farooq Malik
Co-Founder and CEO
Charles Yoo-Naut
Co-Founder and CTO
Recent News
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Company data provided by crunchbase