Senior Machine Learning Engineer, Fraud

This is a fully remote position, open to applicants in Canada.

📋 Description

• You will spearhead the development of innovative fraud prediction models utilizing a combination of methods for tabular, graph, and behavioral data.

• You will construct and enhance feature pipelines and training datasets from both proprietary and third-party signals, collaborating with data and platform teams as necessary.

• You will experiment with new modeling concepts and features, conduct offline experiments, and implement the most effective approaches into production with suitable risk controls.

• You will operationalize models by integrating them into batch and/or real-time decision systems, while enhancing reliability, latency, and operational robustness.

• You will monitor and instrument model and data health, assisting in the definition of retraining/backtesting workflows as fraud patterns change.

• You will identify and execute foundational enhancements to the team's model-building processes.

• You will work collaboratively with Engineering, Fraud Analytics, Product, and ML Platform to establish requirements, assess tradeoffs, and effectively communicate results to both technical and non-technical stakeholders.

⛳️ Requirements

• 6+ years of experience in researching, training, tuning, and deploying ML models at scale, with a relevant PhD accounting for up to 2 years of experience.

• Proven track record of delivering impactful machine learning models in a low-latency live environment.

• Proficient in Python with experience in writing production-quality code.

• Experience in building and assessing models for tabular classification tasks, preferably using gradient-boosted decision trees like LightGBM/XGBoost/CatBoost, or similar.

• Familiarity with a deep learning framework, with a preference for PyTorch.

• Experience in working with distributed data processing or parallel computing frameworks, with Spark being preferred; familiarity with Ray/Dask or similar is also valuable.

• Knowledge of ML lifecycle tools for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).

• Skilled in utilizing AI-powered developer tools (e.g., Claude Code, Cursor, or similar) to enhance iteration, debugging, and code quality in day-to-day development activities.

• Proven ability to transform a straightforward problem or business scenario into a solution that interacts with multiple software components, executing it by writing clear, easily understandable, well-tested, and extensible code.

• Comfort navigating a large codebase, debugging the code of others, and providing constructive feedback to peers through code reviews.

• Your experience reflects a commitment to personal growth, actively seeking feedback from your team, manager, and stakeholders.

• You possess strong verbal and written communication skills that facilitate 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.