Laura Funderburk works as a Developer Advocate for Ploomber, an organization focused on improving the MLOps lifecycle. As a Developer Advocate, Laura combines her passion for MLOps, SQL, and data engineering, with her love for community outreach. Prior to this, Laura held positions as a Data Scientist and DevOps engineer in a variety of settings, including academia, non-for-profit and private sectors. Laura obtained a Machine Learning Engineering certification from the University of California San Diego, and a Bachelor of Mathematics from Simon Fraser University. Since the introduction of Large Language Models, Laura has dedicated her time to learning how to package, productionize and automate data extraction, processing and retrieval through LLMs and open-source packages, and has found a framework she loves in Haystack. When not immersed in building pipelines and engaging with the open-source community, Laura trains Brazilian Jiu-jitsu.