Brook Wassie

About

I build machine learning systems that go the distance - from first prototype to a production service running real-time predictions at scale. I work across the full ML lifecycle: designing training and evaluation workflows, building the pipelines that keep models fed with clean, reliable data, and deploying that work as APIs and services other systems can call in real time. I'm equally at home on the data engineering and MLOps sides of the work - working with platforms and tools such as Databricks, Snowflake, Airflow, Kubeflow, Docker, and infrastructure-as-code with Terraform - and increasingly in generative AI, where I've fine-tuned and applied foundation LLMs for structured information extraction, iterating on prompts and output schemas until the results were something a business could actually rely on. What ties this together is a habit of staying with a project past the model itself: understanding the business problem, aligning stakeholders across different functions, and following the work through deployment and monitoring rather than handing off a notebook. That approach has translated into measurable outcomes, including multi-million-dollar savings initiatives built on model

Experience

Education