Kirill Kononovich
R&D Engineer (Machine Learning) at Grymala
Minsk, Belarus
Summary
🤩
Rockstar🎓
Top SchoolKirill Kononovich is an R&D Machine Learning Engineer with six years of experience blending academic research and practical deployment of ML and computer vision models. Based in Minsk, he transitioned from senior lecturing and civil engineering into hands-on ML work, bringing strong mathematical foundations and an educator’s clarity to complex problems. At Grymala he researches, develops, and deploys CV models on-device, leveraging Python, PyTorch, and production-ready tooling like PostgreSQL and Jupyter. His background in scientific research and a Deep Learning School specialization underpin a methodical approach to model design, evaluation, and optimization. A collaborative team player, he pairs curiosity-driven learning with a track record of helping colleagues translate research into working systems.
6 years of coding experience
Data Science, Machine Learning, Data Science, Machine Learning at Deep Learning School (ФПМИ МФТИ)Магистр технических наук, Civil Engineering, Магистр технических наук, Civil Engineering at Белорусский национальный технический университет
Github Skills (36)
kubernetes10
docker10
continuous-integration10
docker-image10
tuf10
continuous-delivery10
buildah10
gitops10
glossary10
helm10
dockerfile10
golang10
trust10
cloud-native10
devops10
Programming languages (4)
Github contributions (5)
flant/kubernetes-website
Apr 2022 - Mar 2024
Kubernetes website and documentation repo:
Contributions:140 pushes, 19 branches in 1 year 11 months
kubernetes
flant/cncf-glossary
Jul 2023 - Mar 2025
The CNCF Cloud Native Glossary Project aims to define cloud native concepts in clear and simple language, making them accessible to anyone — whether they have a technical background or not (https://glossary.cncf.io).
Contributions:1 PR, 170 pushes, 62 branches in 1 year 8 months
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