Fraud ML Engineer — Real-Time Risk & Scale (Equity)

raincards.xyz; New York (NY); On-site; USD 170,000 - 240,000; Full time

Benefits offered by this job

Unlimited time off

Flexible working

Health benefits

401(k) match

Equity plan

Office meals

Team summits

Job summary

Rain is hiring a Machine Learning Engineer - Fraud Risk in New York, NY to architect scalable ML systems for fraud detection and real-time risk scoring.

You will build end-to-end ML pipelines, collaborate with data scientists and engineers, and ensure low-latency decisioning with strong data governance and security.

Join a fast-growing fintech team where you will shape risk infrastructure and impact Rain's products and customer trust.

Qualifications

• 5+ years of experience building ML systems in production; at least 2+ in fraud, risk, or anomaly detection
• Degree in CS/Engineering/Statistics/Applied Math or related field
• Proven track record designing and maintaining ML models at scale
• Strong knowledge of supervised/unsupervised learning and anomaly detection
• Ability to work autonomously and collaborate with data scientists to translate models into fraud prevention systems
• Experience deploying real-time fraud detection models in production

Responsibilities

• Architect and build scalable ML systems for fraud detection and anomaly detection
• Develop end-to-end ML pipelines: data ingestion, feature engineering, model training, deployment
• Design and implement low-latency, real-time decision systems
• Own ML infrastructure, including model versioning, automated retraining, and safe deployment
• 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 ML development lifecycle
• Partner with platform teams to meet strict SLAs for availability, latency, and accuracy
• Collaborate closely with engineers, data scientists 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

Skills

ML Systems in Production

Fraud Detection

Statistics / Modeling

Communication

Autonomous Work

Cross-functional Collaboration

Education

Bachelor's degree in CS/Engineering/Statistics/Applied Math

Tools

Python

PyTorch

TensorFlow

scikit-learn

Job description

Rain is hiring a Machine Learning Engineer - Fraud Risk in New York, NY to architect scalable ML systems for fraud detection and real-time risk scoring.

You will build end-to-end ML pipelines, collaborate with data scientists and engineers, and ensure low-latency decisioning with strong data governance and security.

Join a fast-growing fintech team where you will shape risk infrastructure and impact Rain's products and customer trust.