Senior Machine Learning Engineer (Fraud ML)
New
Remote CanadaFull-TimeSenior
SalaryCAD 150000 - 200000 / year
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Job Details
- Experience
- 6+ years
- Required Skills
- PythonKubeflowMachine LearningMLFlowPyTorchAirflowSpark
Requirements
- 6+ years experience researching, training, tuning, and launching ML models at scale.
- Track record of delivering high impact machine learning models in a low latency live setting.
- Strong Python skills and experience writing production-quality code.
- Experience building and evaluating models for tabular classification problems.
- Experience with a deep learning framework (PyTorch preferred).
- Experience working with distributed data processing or parallel compute frameworks (Spark, Ray, or Dask).
- Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow).
- Proficiency using AI-powered developer tools (e.g., Claude Code, Cursor) to accelerate development.
- Ability to navigate a large code base and provide feedback through code reviews.
- Strong verbal and written communication skills.
Responsibilities
- Lead development of new fraud prediction models using a mix of approaches for 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 the best-performing approaches into production.
- Integrate models into batch and/or real-time decision systems to improve reliability, latency, and operational robustness.
- Instrument and monitor model and data health, and help define retraining/backtesting workflows.
- Collaborate across Engineering, Fraud Analytics, Product, and ML Platform to define requirements and evaluate tradeoffs.
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