Daniil Chesakov
GenAI Field Solutions Architect at Google
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolDaniil Chesakov is a GenAI Field Solutions Architect in London with nine years of experience building and deploying ML systems across industry and research settings. He combines deep technical expertise in deep learning, LLMs, Docker and Python with hands-on production work—from leading a FaceSwap project that gained 1K+ GitHub stars and ONNX productionization to scaling BERT/RAG solutions handling millions of requests at McKinsey’s QuantumBlack. He has driven measurable business impact across domains (£10M+ network improvements, fraud detection, clinical lead generation) and has led teams as a senior ML engineer. A Skoltech master’s graduate and UK Global Talent Visa holder, Daniil is equally comfortable translating complex data into product strategy and improving inference pipelines, including audio/video processing and super-resolution.
9 years of coding experience
6 years of employment as a software developer
Bachelor's degree Economics, Bachelor's degree Economics at Higher School of EconomicsData Science, Data Science at Yandex School of Data AnalysisBachelor's degree Economics, Bachelor's degree Economics at New Economic SchoolMaster's degree Computer science, Master's degree Computer science at Skolkovo Institute of Science and TechnologyЛицей "Вторая школа"
Github Skills (7)
computer-vision10
pytorch10
deeplearning-ai10
deep-learning10
python10
opencv9
ffmpeg8
Programming languages (3)
Github contributions (5)
ai-forever/ghost
Dec 2021 - Dec 2021
A new one shot face swap approach for image and video domains
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 11 commits, 10 PRs in 15 days
Contributions summary:Daniil contributed to the core inference pipeline of the project, adding crucial functionalities to the video processing module. They implemented the loading of model weights, including a model for eye loss. The user also introduced an inference notebook and made modifications to the super-resolution model usage. Furthermore, they incorporated audio processing, including the integration of audio from another video and added supporting files for model training.
computer-visiondeep-face-swapdeep-learningdeepfakeface-swap
Danyache/skoltech_image_cap
May 2020 - Jun 2020
Contributions:39 commits, 36 pushes, 1 branch in 21 days
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.