Senior MLOps Engineer

Summary

Owns and operates the ML infrastructure and platform powering forecasting and risk products, including experiment tracking, model registry/lineage, IaC, CI/CD for ML pipelines, reproducible training, automated validation, and safe rollouts. Collaborates with Data Science, Data Engineering, and Security to harden the data lakehouse, improve storage and observability, and produce architecture documentation and runbooks to support cross-functional teams.