Miguel Mejia

Miguel Mejia has a diverse work experience in the field of software development and artificial intelligence. Miguel began their career at Bouquet Collection in 2013, where they were responsible for developing and maintaining the company's SCM software. From 2014 to 2015, they worked at Globo Studio as a Software Developer, contributing to the development and maintenance of the company's SCM software using Visual Basic, C#, and Microsoft SQL Server.

In 2015, Miguel joined SproutLoud Media Networks as a Software Developer, where they worked on various software development projects until 2018. Miguel then moved on to Talos Digital, where they gained experience as a Java Software Developer, focusing on the development and maintenance of e-commerce web applications using SAP commerce tools.

In 2020, Miguel started freelancing as an ML & AI Engineer, working on various machine learning and artificial intelligence projects. Miguel contributed their expertise to different clients until 2023.

From 2021 to 2023, Miguel worked at the Digital Americas Pipeline Initiative (DAPI) as an Artificial Intelligence Programmer. In this role, they were responsible for developing and maintaining data procedures and pipelines for the Data as a Service (DaaS) application. Miguel also created a framework to abstract the Spark ETL process and monitored AWS spark applications through EMR.

In 2023, Miguel joined Bearing as a Machine Learning Engineer, expanding their expertise in the field of machine learning.

Miguel Mejia obtained their Bachelor's degree in Computer Software Engineering from Universidad EAFIT, where they studied from 2009 to 2017. Following that, they pursued a Master of Science degree in Data Science and Analytics from the same university starting in 2019. In terms of certifications, Miguel obtained an EFSET English Certificate with a proficiency level of C2 from EF Standard English Test in September 2020. Additionally, they also received a SAFe practitioner certification from Scaled Agile, Inc. in October 2016.