Machine Learning Engineer - Fraud Risk

📋 Description

• Architect scalable ML systems for fraud, anomaly, and behavior
• Build end-to-end ML pipelines: ingestion, features, training, deployment
• Design low-latency, real-time decision systems with streams
• Own ML infrastructure: versioning, retraining, safe deployment
• Create monitoring and alerts for performance, latency, data quality
• Lead experiments on explainability, drift, and robustness for fraud

🎯 Requirements

• 5+ years building production ML; 2+ in fraud/risk
• Degree in CS, Engineering, Stats or related field
• Proven track record designing scalable ML models
• Python with ML frameworks: PyTorch, TensorFlow, scikit-learn
• Strong knowledge of supervised/unsupervised learning and anomaly detection
• Autonomous, able to work with ambiguity; collaborate with data scientists
• Experience deploying real-time and offline fraud models
• Cross-functional deployment of ML solutions at scale

🎁 Benefits

• Salary USD 187k–258.7k per year
• Equity and bonus eligibility
• Unlimited vacation with minimum 10 days
• Flexible work setup; home/office stipend
• Health, dental, vision for you and dependents
• 401(k) with 4% company match