Affirm
Machine Learning Engineer II (Underwriting ML)
Remote Canada +1 · Remote · Full-time · Posted Aug 6, 2026
- Location
- Remote Canada
Remote US - 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 make real-time underwriting decisions by assessing transaction repayment risk and expected value.
What you'll do
- Develop underwriting prediction models and build feature pipelines and training datasets.
- Prototype and evaluate modeling approaches, then productionize them in batch or real-time decision systems with risk controls.
- Monitor model and data health and help define retraining and backtesting workflows.
What they ask for
- 2+ years of experience as a machine learning engineer or a PhD in a relevant field.
- Strong Python skills and experience writing production-quality code.
- Experience building and evaluating classification models, using a deep learning framework, and working with distributed data processing or parallel compute frameworks.
- Proficiency using AI-powered developer tools in day-to-day development workflows.
Nice to have
- Gradient-boosted decision trees such as LightGBM, XGBoost, or CatBoost; PyTorch; Spark; Kubeflow, Airflow, or MLflow are listed as preferred examples.
Pay
$133,000 - $183,000 CAD base salary per year
Tools
Python, LightGBM, XGBoost, CatBoost, PyTorch, Spark, Ray, Dask
AI focus
Develop and productionize underwriting ML models for real-time transaction decisions, assessing repayment risk and expected value; use AI-powered developer tools to accelerate iteration, debugging, and code quality.
Model-written summary · the original posting is authoritative