Michael André
About Michael André
Michael André is a Software Engineer with a background in machine learning and artificial intelligence. He has worked for various companies in Sweden, including Kapsch TrafficCom AG, Zenseact, and Recorded Future, and has a strong academic foundation from Linköping University.
Current Role at Recorded Future
Michael André currently serves as a Software Engineer at Recorded Future, a position he has held since 2022. In this role, he applies his expertise in software development and machine learning to contribute to the company's data-driven security solutions. His work focuses on enhancing the capabilities of Recorded Future's products through innovative software engineering practices.
Previous Experience in Machine Learning Engineering
Prior to his current role, Michael André worked as a Machine Learning Engineer at Zenseact from 2020 to 2022. He was responsible for developing machine learning models to improve autonomous driving technologies. Before that, he held a similar position at Kapsch TrafficCom AG for one year, where he contributed to traffic management solutions through machine learning applications.
Educational Background in Artificial Intelligence
Michael André studied at Linköping University, where he earned a Master of Science in Artificial Intelligence and Machine Learning from 2016 to 2018. His education provided him with a strong foundation in advanced computational techniques and machine learning algorithms. He also completed a Bachelor of Science in Computer Science at the same institution from 2013 to 2016.
Early Career and Teaching Experience
Michael's early career included various roles that contributed to his professional development. He worked as a Mathematics Teacher at Linköping University for three months in 2015, where he taught undergraduate students. Additionally, he served as a Lab Assistant at the university for two years, supporting research and educational activities.
Thesis Work and Software Development Roles
In 2018, Michael André completed his thesis work at Veoneer, focusing on machine learning applications for automotive technologies. He also worked as a Software Developer at Veoneer for five months, where he further developed his skills in software engineering. His experience includes a brief tenure at Autoliv as a Software Developer in 2017.