Machine Learning Engineer II, Fraud

Posted 5 days ago

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About the role

  • Machine Learning Engineer developing fraud prediction models for Affirm. Collaborating with cross-functional teams and building real-time transaction decision systems.

Responsibilities

  • You will develop and iterate on fraud prediction models using a mix of approaches for tabular and behavioral data
  • You will build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed.
  • You will prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
  • You will help productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness.
  • You will instrument and monitor model and data health, and help define retraining/backtesting workflows as fraud patterns evolve.
  • You will collaborate across Engineering, Fraud Analytics, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences.

Requirements

  • You have a total of 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 models for tabular classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost, or similar).
  • Experience with a deep learning framework (PyTorch preferred).
  • Experience working 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 (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).
  • Proficient in using AI-powered developer tools (e.g., Claude Code, Cursor, or similar) to accelerate iteration, debugging, and code quality as part of day-to-day development workflows.
  • You have mastered taking a simple problem or business scenario into a solution that interacts with multiple software components, and executing on it by writing clear, easily understood, well tested and extensible code.
  • You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews.
  • Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
  • You have strong verbal and written communication skills that support effective collaboration with our global engineering team.

Benefits

  • Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
  • Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
  • Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
  • ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount

Job type

Full Time

Experience level

JuniorMid level

Salary

CA$125,000 - CA$175,000 per year

Degree requirement

Professional Certificate

Tech skills

AirflowPythonPyTorchRaySpark

Location requirements

RemoteCanada

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