Eniola Ajiboye is a software engineer based in London transitioning from three years of front-end web development into applied machine learning across the software stack, now working at Google. With 11 years in tech, she blends production front-end expertise—building accessible, responsive, and secure web apps and internal metric dashboards—with hands-on ML experience from a CMU MSIT in Applied Machine Learning. Her projects include shrinking a Pix2Pix model from 217MB to 8MB for offline mobile use and shipping a Kotlin/Jetpack Compose app that captured training data via passwordless Firebase sync. She has driven product expansion and operational improvements at companies like Opera and led integrations and prototyping at scale, showing a knack for turning prototypes into production features. Notably, she pairs UI/UX sensitivity with practical ML deployment experience, making models usable in constrained, real-world mobile contexts.
10 years of coding experience
4 years of employment as a software developer
Bachelor’s Degree Computer Science, Bachelor’s Degree Computer Science at Redeemer's University
Mobile Web Specialist Nanodegree Software Development, Mobile Web Specialist Nanodegree Software Development at Udacity
Master of Science - MSIT Applied Machine Learning, Master of Science - MSIT Applied Machine Learning at Carnegie Mellon University
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