Summary
Yesid Lopez is a Machine Learning Engineer based in Berlin with 8 years of experience building and operationalizing AI systems that scale in production. He blends deep ML deployment skills—Kubeflow, RAG recommender systems, LLMs and high-traffic inference—with a strong foundation in Software QA, having led testing strategies and introduced BDD and metrics-driven quality across teams. At Wolt he supports multiple teams deploying traffic-sensitive models, and previously drove MLOps and edge CV projects, demonstrating both model and infrastructure fluency. His background as an instructor and QA lead gives him a disciplined, test-first mindset that reduces drift and improves reliability in AI pipelines. Known for making AI solutions maintainable and impactful, he’s motivated by experiments that marry generative AI with practical engineering constraints.
8 years of coding experience
5 years of employment as a software developer
Master's degree Data Science, Master's degree Data Science at Universidad Icesi
English, Spanish, German