Senior Machine Learning Operations Engineer

Design, build, and operate scalable backend services, APIs, and data pipelines. Improve the reliability, performance, and observability of production ML and optimization systems. Own the path from trained model to production: model versioning and registry (MLflow), safe rollout and rollback, and monitoring for data quality and model drift. Build clean interfaces that let new ML models and decisioning capabilities integrate safely and efficiently, including experimentation and feature-flag tooling. Strengthen engineering foundations across a growing codebase: automated testing, type checking, CI/CD, infrastructure as code, documentation, and thoughtful system design. Profile data-heavy services and pipelines; reduce execution time and memory footprint where it matters. Collaborate with data scientists, operations researchers, and product engineers to translate business needs into robust technical solutions.