Building and improving machine learning systems for real-time transaction decisions, the full-time remote Machine Learning Engineer II will develop underwriting prediction models, scale feature pipelines, and collaborate across teams to productionize models while ensuring their health and performance. Key responsibilities Develop and iterate on underwriting prediction models using various approaches for tabular and sequential data Build and scale feature pipelines and training datasets, collaborating with data and platform teams as needed Prototype modeling ideas, run offline experiments, and integrate models into decision systems with a focus on reliability and operational robustness Required qualifications 2+ years of experience as a machine learning engineer or a PhD in a relevant field Strong Python skills with experience in writing production-quality code Experience with classification models and deep learning frameworks, preferably PyTorch Familiarity with distributed data processing frameworks, such as Spark Knowledge of ML lifecycle tooling for training orchestration and model monitoring (e.g., Kubeflow, Airflow)