Santiago Soares
About Santiago Soares
Santiago Soares is a Software Engineer with extensive experience in machine learning and telecommunications. He currently works at WiLine Networks and has previously held positions at Embraer, Vivo, GVT, and Hilab.
Work at WiLine
Santiago Soares has been employed at WiLine Networks as a Software Engineer since 2022. His role involves leveraging his technical skills in software development to enhance the company's network solutions. WiLine Networks is known for providing high-speed internet and telecommunications services, and Soares contributes to the development of innovative software that supports these offerings.
Education and Expertise
Santiago Soares holds a Master's degree in Aeronautics/Telecommunications from Instituto Tecnológico de Aeronáutica - ITA, where he studied from 2007 to 2010. He also completed a specialization in Computer Networks/Telecommunications at Centro Federal de Educação Tecnológica do Paraná - CEFET-PR from 2006 to 2007. Additionally, he earned a Machine Learning Engineer Nanodegree from Udacity between 2020 and 2021. His educational background supports his expertise in TCP/IP networks, machine learning, and MLOps.
Professional Background
Santiago Soares has a diverse professional background in the telecommunications and software engineering sectors. He began his career as a VoIP Analyst at GVT in 2006, later transitioning to a Telecom Specialist role until 2016. He then worked at Vivo (Telefônica Brasil) as a Device Development Specialist from 2016 to 2021. Following this, he served as a Machine Learning Analyst at Hilab for nine months before joining WiLine Networks. His experiences have equipped him with a comprehensive understanding of both telecommunications and software development.
Achievements in Machine Learning
Santiago Soares has developed significant expertise in deploying machine learning models, particularly using AWS services such as Sagemaker, Lambda functions, Step Functions, and S3. He has also implemented CI/CD pipelines specifically designed for machine learning applications, demonstrating his capability to integrate machine learning processes into production environments effectively. His skills in this area are complemented by a strong foundation in TCP/IP networks.