who can bring their depth and breadth of experience in applied data science and optimization at industry scale to help guide our Index-wide technology strategy for machine learning and optimization, and to drive pragmatic execution and iterative improvement of the same.
Responsibilities
Design and implement enterprise-scale MLOps systems and platforms (including data ingestion, feature pipelines, model training, validation, deployment and monitoring), setting standards for high-performance ML products.
Productionalize and support scalable and efficient Machine Learning models and solutions.
Define and enforce standards for model lifecycle management, including versioning, monitoring, alerting, traceability and highly available low-latency inference systems.
Refine and contribute to advanced data management strategies, optimizing for performance given extens...