Alex Kim has spent most of his career solving data science problems across a wide range of domains, including physics, aerospace, telemetry and log analytics, and image and video processing. Working across such different fields taught him a lesson that stays constant: a model only creates value once it reliably runs in production.

That realization pulled him toward the engineering side of machine learning, focusing on the processes and tools needed to take a project from an idea to a production solution. Today, he works as an MLOps Solutions Engineer at Iterative.ai, helping customers extract the most value from the Iterative ecosystem of tools for versioning data, tracking experiments, and organizing ML workflows.

This combination of hands-on data science experience across domains and applied MLOps expertise makes Alex a frequent, practical voice on bridging the gap between experimentation and production machine learning.