Machine Learning Engineer - Fraud Risk
Rain(25 days ago)
About this role
A Machine Learning Engineer - Fraud Risk at Rain is responsible for architecting and building scalable ML systems focused on fraud detection, anomaly detection, and behavioral analysis. This role includes developing end-to-end ML pipelines, implementing real-time decision systems, and maintaining ML infrastructure for model monitoring and performance. Collaboration with cross-functional teams is essential to integrate ML models effectively within the transaction ecosystem, while also leading experimentation on model robustness and explainability in a fast-paced environment. The ideal candidate should have at least 5 years of production ML experience, particularly in fraud or risk domains, and expertise in Python and ML frameworks.
Required Skills
- ML Systems
- Fraud Detection
- Anomaly Detection
- Behavioral Analysis
- Data Ingestion
- Feature Engineering
- Model Training
- Deployment Monitoring
- Decision Systems
- Model Versioning
+12 more
Qualifications
- Degree in Computer Science, Engineering, Statistics, Applied Math, or a related technical field
- 5+ years of experience building ML systems in production; at least 2+ in fraud, risk, or anomaly detection domains
- Advanced proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
- A graduate degree in Computer Science, Engineering, Statistics, Applied Math, or a related technical field (nice to have)
About Rain
www.rain.xyzRain is a financial technology company that specializes in stablecoin-powered cards and payments infrastructure. Their platform offers a comprehensive suite of APIs that empower businesses to issue stablecoin-backed cards, facilitate global transactions, and provide digital wallet solutions with speed and compliance. With a focus on creating modern financial experiences, Rain serves fintech companies, neobanks, and developers, enabling them to integrate seamless payment solutions across more than 150 countries. Founded in 2021, Rain is committed to transforming the financial landscape through innovative technology and robust support for its partners.
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