Vlad Yushchenko
About Vlad Yushchenko
Vlad Yushchenko is a Sr. Machine Learning Engineer currently working at CAPE Analytics in Munich, Bavaria, Germany. He has extensive experience in machine learning model deployment and product development, with a background that includes positions at intive and AGT International.
Work at CAPE Analytics
Vlad Yushchenko has been employed at CAPE Analytics as a Senior Machine Learning Engineer since 2021. In this role, he focuses on deploying machine learning models, which is essential for the company's operations. His expertise contributes to the development of innovative solutions in the field of analytics, particularly in relation to computer vision and model deployment.
Previous Experience in Machine Learning
Prior to his current position, Vlad Yushchenko worked as a Machine Learning Engineer at intive from 2019 to 2021 in the Munich Area, Germany. His responsibilities included implementing machine learning solutions and enhancing product features. Additionally, he served as a Computer Vision Engineer at AGT International from 2017 to 2019, where he specialized in computer vision technologies.
Education and Expertise
Vlad Yushchenko holds a Bachelor of Science (B.Sc.) in System Analysis from the National Technical University of Ukraine 'Kyiv Polytechnic Institute', where he studied from 2011 to 2015. He furthered his education by obtaining a Master's degree in Computer Science from Friedrich Schiller University Jena in 2016, followed by a Master of Science (M.Sc.) in Computer Science from Technische Universität Darmstadt from 2016 to 2019.
Internship Experience
Vlad Yushchenko gained early experience as a System Analyst Intern at the World Data Center for Geoinformatics and Sustainable Development in 2014. This internship lasted for one month in Kiev, Ukraine, and provided him with foundational skills in system analysis and data management.
Focus on Product Development
Vlad Yushchenko has a strong focus on productizing research ideas and shipping products at scale. His interests lie particularly in machine learning and artificial intelligence, where he aims to develop practical applications that leverage advanced technologies for real-world use.