Machine Learning Engineer - Fraud Risk

Rain; New York (NY); Hybrid; USD 50,000 - 999,000; Full time

Benefits offered by this job

Unlimited time off

Flexible working

Comprehensive health, dental, and vision plans

401(k) with a 4% company match

Equity options

Company card for product testing

Access to gym memberships and wellness programs

Domestic and international team summits

Job summary

Rain is seeking an experienced Machine Learning Engineer with a focus on fraud detection to build scalable ML systems. The ideal candidate will have over 5 years of experience in production-level ML, advanced skills in Python and frameworks such as PyTorch and TensorFlow. Responsibilities include architecting ML systems, maintaining ML pipelines, and collaborating with cross-functional teams. Benefits include unlimited time off, flexible work arrangements, and comprehensive health plans.

Qualifications

• 5+ years of experience building ML systems in production, with 2+ years in fraud detection.
• Experience developing predictive real-time and offline fraud detection models.
• Proven track record designing and maintaining ML models at scale.

Responsibilities

• Architect and build scalable ML systems for fraud detection.
• Develop and maintain end-to-end ML pipelines.
• Design and implement low-latency decision systems.

Skills

Building ML systems in production

Fraud detection

Python

ML frameworks (PyTorch, TensorFlow)

Statistical modeling

Education

Degree in Computer Science/Engineering/Statistics/Applied Math

Job description

About The Company

Rain makes the next generation of payments possible across the globe. We’re a lean and mighty team of passionate builders and veteran founders. Our infrastructure makes stablecoins usable in the real‑world by powering card transactions, cross‑border payments, B2B purchases, remittances, and more. We partner with fintechs, neobanks, and institutions to help them launch solutions that are global, inclusive, and efficient. You will have the opportunity to deliver massive impact at a hypergrowth company funded by top investors in fintech, crypto, and SaaS.

Our Ethos

We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company.

About The Team

The fraud risk management team at Rain creates sophisticated, scalable risk mitigation solutions to protect our customers and deliver a low‑friction experience. We achieve this by maintaining transaction and lifecycle event monitoring, building alerts to speed fraud detection and response, and creating risk rules and strategies powered by ML models. We are a pillar of the business, supporting new products and ensuring their success. Rain’s next‑generation payment technology introduces new fraud vectors that require holistic, end‑to‑end thinking, strong data fundamentals, and fraud management savvy to combat.

What You’ll Do

• 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 such as shadow and 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 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

What We’re Looking For

• 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 such as PyTorch, TensorFlow, and 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 ML solutions at scale

Nice to have, but not mandatory

• 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 – we require all team members to take at least 10 days off
• Flexible working – you may work from home or from the office as you prefer
• Easy to access benefits – comprehensive health, dental, and vision plans for U.S. team members and a 100% company‑subsidized life insurance plan
• Retirement goals – 401(k) with a 4% company match
• Equity plan – equity options for all team members
• Rain Cards – a company card for testing our core products and services
• Health and Wellness – access to gym memberships, fitness classes, massages, and other wellness spending through the company card
• Team summits – domestic and international off‑sites to strengthen relationships and build a common vision

Compensation Range: $50,000 - $999,000