Machine Learning Engineer II (Underwriting ML)

Responsibilities

• You will develop and iterate on underwriting prediction models using a mix of approaches for tabular and sequential 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
• You will collaborate across Engineering, Risk Analytics, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences.
• What we look for
• 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 classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost, or similar).

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