Farid Delgado Molina
About Farid Delgado Molina
Farid Delgado Molina is a Lead Software Engineer at Thomson Reuters in Toronto, Canada, with a background in Computer Science from Universidad del Norte. He has extensive experience in developing machine learning workflows and has worked in various roles, including as a Java Developer and Systems Analyst.
Work at Thomson Reuters
Farid Delgado Molina serves as a Lead Software Engineer at Thomson Reuters, a position he has held since 2019. In this role, he focuses on developing and implementing advanced software solutions. His work involves creating end-to-end machine learning production workflows, particularly for question answering systems. He employs supervised machine learning and deep learning models to enhance the functionality of various applications. His contributions are integral to the company's efforts in leveraging machine learning to improve user experience and operational efficiency.
Education and Expertise
Farid Delgado Molina earned a Bachelor of Science in Engineering with a focus on Computer Science from Universidad del Norte, completing his studies from 2007 to 2011. He furthered his education by obtaining a Postgraduate Diploma in Computer Software Engineering from the same institution, studying from 2012 to 2013. His academic background provides a solid foundation for his expertise in software development and machine learning.
Background
Prior to his current role at Thomson Reuters, Farid Delgado Molina worked as a Java Developer at Universidad del Norte for 11 months in 2011. He then transitioned to Puerto de Barranquilla, Sociedad Portuaria, where he served as a Systems Analyst for seven years, from 2012 to 2019. His experience in these positions contributed to his skill set in software engineering and systems analysis.
Achievements in Machine Learning Development
Farid Delgado Molina has made significant contributions to machine learning development. He developed end-to-end production workflows specifically for question answering systems and migrated MPNet-based deep learning model tasks from Python to Java. He designed a silver data processing pipeline for autonomous machine learning and contributed to the development of supervised models that enhance features for search and question suggestion engines.
Technical Skills and Tools
Farid Delgado Molina utilizes a range of tools and technologies in his work, including Spark, AWS Glue/EMR, Elasticsearch, Hadoop, and Hive. These tools enable him to process large datasets effectively and implement machine learning solutions. His proficiency in various programming languages and frameworks supports his versatility in software development.