Stanislav Bondarenko
About Stanislav Bondarenko
Stanislav Bondarenko is a software engineer with experience in various roles, including positions at Nevercode and Glia. He holds multiple degrees in computer engineering and software engineering from notable universities and has a strong interest in machine learning.
Work at Glia
Stanislav Bondarenko has been employed at Glia as a Software Engineer since 2021. In this role, he is involved in software development and engineering tasks, contributing to the company's projects and initiatives. His expertise includes working with Kubernetes configuration, utilizing Helm charts, and managing various aspects of software deployment.
Previous Experience at Nevercode
Before joining Glia, Stanislav worked at Nevercode as a Software Engineer from 2019 to 2021. His tenure at Nevercode lasted for two years and took place in Tartu. During this time, he developed software solutions and contributed to the engineering team.
Experience at Materialise
Stanislav Bondarenko held the position of Medical Conversion Engineer at Materialise for seven months in 2018, based in Kyiv City, Ukraine. He also worked as a Trainee Medical Conversion Engineer at the same company for two months in 2017. His responsibilities included tasks related to medical software engineering.
Educational Background
Stanislav earned a Bachelor's degree in Computer Sciences from the National Technical University of Ukraine 'Kyiv Polytechnic Institute', completing his studies from 2014 to 2018. He also holds a Bachelor's degree in Computer Engineering from Orta Doğu Teknik Üniversitesi / Middle East Technical University, achieved in 2017. Additionally, he obtained two Master's degrees in Computer Software Engineering from the University of Tartu and TalTech – Tallinn University of Technology, both completed between 2018 and 2020.
Technical Skills and Interests
Stanislav has experience in configuring AWS and Snowflake using Terraform, as well as handling small fixes for dockerfiles and Ansible playbooks. He has a hobby interest in machine learning and has pursued courses in machine learning and neural networks. His master's thesis focused on predicting a movie's box office using pre-release data.