About

Joshua Isaac Pabilona is a seasoned Lead Machine Learning Engineer with expertise in every aspect of the ML pipeline. He has substantial hands-on experience in data collection, visualization, analysis, preprocessing, augmentation, model production, designing network topologies, hyperparameter tuning, thorough model validation, and evaluation. Joshua is also a devout practitioner of MLOps, a DevOps approach to ML workflows. Currently working as a Software Engineer Intern at Orange and Bronze Software Labs, Joshua has previously worked as a Machine Learning Engineer and Lead Machine Learning Engineer at InnoVantage, Inc. During his tenure at InnoVantage, Joshua built various end-to-end models in computer vision and natural language processing. He architected a system that is currently in use for sustainably serving containerized ML models queried by API endpoints. He also created a named entity recognition (NER) system, a sentiment analysis system, and a semantic sentence similarity (STS) system for unstructured English, Tagalog, and Taglish text. Joshua deployed end-to-end computer vision models for solving various CAPTCHAs that block RPA workflows. Additionally, he developed a POC chatbot for a home shopping network and a proprietary web scraping program that automatically generates PASCAL VOC datasets for training UI component detection models. Joshua holds a Bachelor of Science degree in Computer Science, majoring in Statistics from the University of the Philippines. He has a strong technical background in ML, Computer Vision, Hyperparameter, NLP, Sentiment Analysis, Research Scientist, DevOps, UI, Web, and Software Engineering. With 4.19 years of relevant experience, Joshua is a highly skilled and accomplished professional in the field of Machine Learning Engineering.