Machine Learning Engineer II (Underwriting ML)

What you'll do - 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). - Experience with a deep learning framework (PyTorch preferred). - Experience working with distributed data processing or parallel compute frameworks (Spark preferred; Ray/Dask or similar). - Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms). - Proficient in using AI-powered developer tools (e.g., Claude Code, Cursor, or similar) to accelerate iteration, debugging, and code quality as part of day-to-day development workflows. - You have mastered taking a simple problem or business scenario into a solution that interacts with multiple software components, and executing on it by writing clear, easily understood, well tested and extensible code. - You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews. - Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders. - You have strong verbal and written communication skills that support effective collaboration with our global engineering team. - This position requires either equivalent practical experience or a Bachelor's degree in a related field

USA base pay range (CA, WA, NY, NJ, CT) per year: $165,000 - $225,000 USA base pay range (all other U.S. states) per year: $146,000 - $206,000