About the company
Affirm provides a clear, predictable way to pay over time, with no hidden fees and no surprises. On the ML Fraud team, you'll build and improve machine learning systems that make real-time transaction decisions.
Responsibilities
- Lead development of new fraud prediction models using tabular, graph, and behavioral data
- Build and scale feature pipelines and training datasets from proprietary and third-party signals
- Prototype new modeling ideas and features, run offline experiments, and drive best-performing approaches into production
- Productionize models: integrate into batch and/or real-time decision systems, improve reliability, latency, and operational robustness
- Instrument and monitor model and data health, define retraining/backtesting workflows
- Identify and implement foundational improvements to how the team builds models
- Collaborate across Engineering, Fraud Analytics, Product, and ML Platform
Requirements
- 6+ years experience researching, training, tuning and launching ML models at scale (relevant PhD can count for up to 2 years)
- Track record of delivering high impact ML models in a low latency live setting
- Strong Python skills and production-quality code
- Experience building and evaluating models for tabular classification problems (LightGBM/XGBoost/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 (Kubeflow, Airflow, MLflow, or equivalent)
- Proficient in AI-powered developer tools (Claude Code, Cursor, or similar)
- Comfortable navigating a large code base and providing feedback through code reviews
- Strong verbal and written communication skills
Conditions
- Remote Canada, open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan
- Base pay range per year: $153,000 - $213,000
- Health coverage at no cost for employees and dependents
- Monthly stipends for tech, health and wellness
- Flexible time off and generous holiday calendars
- Employee stock purchase plan (ESPP)