1848 Ventures, backed by Westfield

Machine Learning Engineer

• Design, train, and deploy production ML models, with emphasis on tree-based methods (XGBoost, LightGBM, CatBoost).
• Contribute to feature engineering and model evaluation approaches that balance accuracy, interpretability, and speed.
• Translate customer needs and product requirements into practical modeling tasks (classification, regression, ranking, uplift).
• Develop custom performance metrics to evaluate models’ ability to generate reasonable counterfactual demand estimates while accounting for varying customer product expectations.
• Support explainability efforts to justify rate decisions with clear artifacts and documentation.
• Build and maintain training and evaluation pipelines, ensuring offline metrics align with online business outcomes.
• Partner with engineering to integrate models into production services and batch jobs with defined SLAs.
• Contribute production ready Python and SQL code with strong testing and review practices.
• Support data quality, observability, and reproducibility across the ML lifecycle.
• Collaborate on experiment design, including A/B testing and staged rollouts.
• Implement policy guardrails to ensure automated rate changes are safe and controlled.
• Analyze experimental results, communicate lift and trade-offs, and document findings.
• Work closely with product, engineering, and leadership to scope problems and propose modeling approaches.
• Participate in code reviews, model reviews, and planning sessions.
• Share learnings and contribute to improving team practices around modeling, metrics, and documentation.

Senior Machine Learning Engineer – Applied Modeling