Affirm
Machine Learning Engineer II (Underwriting ML)
About this role
Build and optimize machine learning models that power real-time underwriting decisions at Affirm, assessing creditworthiness and transaction risk. You'll develop production ML systems using gradient boosting and deep learning, manage feature pipelines, and collaborate with cross-functional teams to deploy models safely and monitor their health in production.
What you'll do
- Develop and iterate on underwriting prediction models using tabular and sequential data techniques
- Build and scale feature pipelines and training datasets from internal and external data sources
- Prototype new modeling approaches, run offline experiments, and deploy high-performing models to production
- Productionize models into batch and real-time decision systems with focus on reliability and latency
- Instrument model and data health monitoring, define retraining and backtesting workflows
- Collaborate across Engineering, Risk, Product, and ML Platform teams to define requirements and communicate results
What they're looking for
- Python and production-quality code
- Gradient-boosted decision trees (LightGBM, XGBoost, CatBoost)
- Deep learning frameworks (PyTorch preferred)
- Distributed data processing (Spark, Ray, or Dask)
- ML lifecycle tooling (Kubeflow, Airflow, MLflow)
- AI-powered developer tools (Claude, Cursor)
- Classification and model evaluation
- Code review and large codebase navigation
Benefits
- 100% subsidized medical, dental, and vision coverage for you and dependents
- Flexible spending wallets for technology, food, and lifestyle needs
- Equity rewards and monthly stipends
- Remote-first work environment
- Generous time off policy
- Family forming expense support
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Affirm
Affirm builds financial infrastructure and platforms that power point-of-sale lending, merchant operations, card issuance, and capital management at scale. The company is hiring backend engineers, AI solutions engineers, and infrastructure specialists to develop reliable, scalable systems for merchant platforms, payment processing, reliability monitoring, and capital orchestration.
- Website
- affirm.com
Likely interview questions
- Walk us through a complex underwriting or risk model you built—how did you approach feature engineering and model selection?
- Describe your experience productionizing ML models; what challenges did you face with latency, scalability, or monitoring?