Machine Learning Engineer II (Underwriting ML)
Core
Build and improve machine learning systems for real-time transaction decisions, assessing repayment risk and expected value for Affirm checkout.
Role type
Machine Learning Engineer II (Underwriting)
Builds
Real-time underwriting models, feature pipelines, and decision systems for consumer buy-now-pay-later transactions.
Domain
Fintech / Credit Risk / Machine Learning
Deliverable
production ML models
Required skills
Python, classification modeling (gradient-boosted trees), deep learning frameworks, distributed data processing, ML lifecycle tooling, AI-powered developer tools
Preferred skills
Experience with proprietary and third-party signals, retraining/backtesting workflows
Technologies
LightGBM, XGBoost, CatBoost, PyTorch, Spark, Ray, Dask, Kubeflow, Airflow, MLflow
Responsibilities
Develop and iterate underwriting prediction models for tabular and sequential data; build and scale feature pipelines; prototype new modeling ideas and drive them to production; integrate models into batch and real-time decision systems; instrument and monitor model and data health; collaborate across Engineering, Risk Analytics, Product, and ML Platform.
Seniority
Mid-level, hands-on IC