Summary
Ednalyn De Dios is a Machine Learning Engineer with nine years of experience designing and operating production-grade AI and automation systems that prioritize governance, observability, and human-in-the-loop controls. She has built end-to-end ML pipelines and MLOps tooling across Azure and AWS, applying NLP, OCR, and predictive modeling to drive measurable business outcomes at companies like Microsoft, Merck, and Intellivo. Her strength is not model tuning but defining clear decision boundaries, exception handling, and roll-back strategies so systems remain legible and defensible under pressure. A former nonprofit IT director and US Navy logistics manager, she brings uncommon operational discipline and stakeholder-first collaboration to technical projects. Based in San Antonio, she blends hands-on engineering with pragmatic governance to turn ambiguous AI initiatives into auditable, production-ready services.
9 years of coding experience
21 years of employment as a software developer
Master of Science - MS Data Analytics, Master of Science - MS Data Analytics at Western Governors University
Certificate of Completion Data Science, Certificate of Completion Data Science at Codeup
English, Tagalog