Senior Machine Learning Engineer (Fraud)
A
AffirmFinancial Technology
Remote CanadaFull-TimeSenior
SalaryCAN base pay range per year: $153,000 - $213,000
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Job Details
- Experience
- 6+ years
- Required Skills
- PythonKubeflowMachine LearningMLFlowPyTorchAirflowSpark
Requirements
- 6+ years of 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 environment.
- Strong Python programming skills and experience writing production-quality code.
- Experience building and evaluating models for tabular classification problems (e.g., LightGBM, XGBoost, CatBoost).
- Experience with a deep learning framework (PyTorch preferred).
- Experience working with distributed data processing or parallel compute frameworks (Spark preferred; Ray/Dask).
- Experience with ML lifecycle tooling (e.g., Kubeflow, Airflow, MLflow).
- Proficient in using AI-powered developer tools like Claude Code or Cursor.
- Ability to navigate large codebases and provide feedback through code reviews.
- Strong verbal and written communication skills.
Responsibilities
- Lead development of new fraud prediction models using tabular, graph, and behavioral data approaches.
- Build and scale feature pipelines and training datasets from proprietary and third-party signals.
- Prototype modeling ideas, run offline experiments, and implement high-performing approaches into production.
- Integrate models into batch and real-time decision systems while improving reliability and latency.
- Instrument and monitor model and data health and define retraining and backtesting workflows.
- Identify and implement foundational improvements to model building processes.
- Collaborate across Engineering, Fraud Analytics, Product, and ML Platform to define requirements and evaluate tradeoffs.
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