Machine Learning Engineer II – Underwriting ML

This is a fully remote position, open to applicants in California, +4 more states.

📋 Description

• Design and refine underwriting prediction models for both tabular and sequential data.

• Construct and enhance feature pipelines and training datasets utilizing proprietary and third-party signals.

• Prototype modeling concepts and features, execute offline experiments, and transition high-performing methods into production with appropriate risk controls.

• Implement models in batch and/or real-time decision-making systems.

• Enhance model reliability, latency, and operational robustness.

• Instrument and oversee model and data health.

• Assist in defining retraining and backtesting workflows.

• Collaborate with Engineering, Risk Analytics, Product, and ML Platform on requirements and tradeoffs.

• Convey results to both technical and non-technical audiences.

⛳️ Requirements

• A minimum of 2 years of experience as a machine learning engineer or a PhD in a relevant discipline.

• Proficient in Python with experience in production-quality coding.

• Demonstrated experience in building and assessing classification models.

• Familiarity with gradient-boosted decision trees like LightGBM, XGBoost, or CatBoost, or equivalent technologies.

• Experience with a deep learning framework; PyTorch is preferred.

• Background in distributed data processing or parallel computing frameworks; Spark is preferred, as well as Ray/Dask or similar tools.

• Experience with ML lifecycle tools for training orchestration, experimentation, and model monitoring, such as Kubeflow, Airflow, MLflow, or comparable internal platforms.

• Proficiency in AI-powered developer tools like Claude Code, Cursor, or similar applications.

• Capability to design solutions involving multiple software components and produce clear, well-tested, and extensible code.

• Comfort in navigating large codebases, troubleshooting others' code, and performing code reviews.

• Strong verbal and written communication skills.

• Equivalent practical experience or a Bachelor's degree in a related field.

🏝️ Benefits

• Equity rewards may be part of the total compensation package.

• Monthly stipends available for health, wellness, and technology expenses.

• Comprehensive health care coverage with all premiums paid for all levels of coverage for you and your dependents.

• Flexible Spending Wallets with stipends for Technology, Food, various Lifestyle needs, and family planning expenses.

• Competitive vacation and holiday policies.

• Employee stock purchase plan allowing employees to acquire shares of Affirm at a discount.

• Reasonable accommodations provided during the hiring process.