Machine Learning Engineer II developing production ML models for Affirm’s pay - over - time platform. Building credit decisioning systems, scalable pipelines, and algorithms that predict default and guide approvals.
About the role
- Machine learning engineer developing real-time underwriting models for Affirm’s buy-now-pay-later platform. Productionizing risk systems, feature pipelines, monitoring, and experimentation workflows.
Responsibilities
- Develop and iterate on underwriting prediction models for tabular and sequential data
- Build and scale feature pipelines and training datasets using proprietary and third-party signals
- Prototype modeling ideas and features, run offline experiments, and move strong approaches into production with risk controls
- Productionize models in batch and/or real-time decision systems
- Improve model reliability, latency, and operational robustness
- Instrument and monitor model and data health
- Help define retraining and backtesting workflows
- Collaborate with Engineering, Risk Analytics, Product, and ML Platform
- Define requirements, evaluate tradeoffs, and communicate results to technical and non-technical audiences
Requirements
- 2+ years of experience as a machine learning engineer or a PhD in a relevant field
- Strong Python skills and production-quality coding experience
- Experience building and evaluating classification models
- Experience with gradient-boosted decision trees such as LightGBM, XGBoost, or CatBoost, or similar
- Experience with a deep learning framework; PyTorch preferred
- Experience with distributed data processing or parallel compute frameworks; Spark preferred, Ray/Dask or similar
- Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, Airflow, or MLflow
- Proficiency using AI-powered developer tools such as Claude Code or Cursor
- Ability to turn business scenarios into solutions spanning multiple software components
- Clear, well-tested, extensible coding practices
- Ability to navigate large codebases, debug others' code, and provide code-review feedback
- Strong verbal and written communication skills
- Equivalent practical experience or a Bachelor’s degree in a related field
Benefits
- Monthly stipends for health, wellness and tech spending
- 100% subsidized medical coverage, dental and vision for you and your dependents
- Health care coverage with all premiums covered for all levels of coverage for you and your dependents
- Flexible Spending Wallets with stipends for Technology, Food, Lifestyle needs, and family forming expenses
- Competitive vacation and holiday schedules
- ESPP enabling employees to buy Affirm shares at a discount
- Reasonable accommodations during the hiring process
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