Affirm
Machine Learning Engineer II (Underwriting ML)
$146K–$225K
Remote US +1 · Remote · Full-time · Posted Aug 6, 2026
- Location
- Remote US
Remote Canada - Experience
- 2+ years as a machine learning engineer or a PhD in a relevant field.
- Education
- Equivalent practical experience or a Bachelor’s degree in a related field.
About the job
Build, deploy, and monitor machine learning systems that assess repayment risk and expected value for real-time Affirm checkout decisions.
What you'll do
- Develop underwriting prediction models and build feature pipelines and training datasets.
- Prototype and evaluate models, then deploy them to batch or real-time decision systems with risk controls.
- Monitor model and data health, improve system reliability, and help define retraining and backtesting workflows.
What they ask for
- Strong Python skills and production-quality coding experience.
- Experience building and evaluating classification models.
- Experience with a deep learning framework.
- Experience with distributed data processing or parallel compute frameworks and ML lifecycle tooling.
Nice to have
- Gradient-boosted decision trees such as LightGBM, XGBoost, or CatBoost; PyTorch; Spark.
- Experience with Kubeflow, Airflow, MLflow, or equivalent internal platforms.
Pay
$165,000 - $225,000 USD base salary; $146,000 - $206,000 USD base salary
Tools
Python, LightGBM, XGBoost, CatBoost, PyTorch, Spark, Ray, Dask
AI focus
Develop underwriting models for repayment-risk and expected-value predictions; use AI-powered developer tools such as Claude Code or Cursor to accelerate iteration, debugging, and code quality.
Model-written summary · the original posting is authoritative