Sergei Laktionov
Member Of Engineering at poolside
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolSergei Laktionov is a Member of Engineering in London with a decade of experience at the intersection of machine learning, quantitative research, and economics. He has applied ML and computer vision in industry roles and now focuses on LLM post-training and agentic reinforcement learning, blending hands-on engineering with research rigor. Sergei has taught reinforcement learning and delivered practical ML coursework to master's students, demonstrating an ability to translate advanced theory into usable workflows. His background in mathematics, advanced machine learning (HSE), and economics/data science (NES, Yandex School) enables a multi-disciplinary approach to problem solving. He is an ML enthusiast with a particular interest in reinforcement learning, and his career shows a steady progression from quant internships to production-focused applied science. Beyond models, he brings a quantitative lens to product problems, often bridging academic methods and production constraints.
10 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Mathematics and Computer Science, Bachelor's degree, Mathematics and Computer Science at Saint Petersburg State UniversityMaster's degree, Advanced Machine Learning, Master's degree, Advanced Machine Learning at Higher School of EconomicsEconomics and Data Science, Economics and Data Science at New Economic SchoolData Science, Data Science at Yandex School of Data Analysis
Github Skills (13)
keras10
deep-reinforcement-learning10
pytorch10
markov-decision-processes10
deep-learning10
reinforcement-learning10
monte-carlo-tree-search10
tensorflow9
api8
reinforcement-learning-environments7
q-learning6
agent5
gymnasium5
Programming languages (2)
Github contributions (5)
laktionov/RL-course
Oct 2022 - Mar 2023
Contributions:62 commits, 124 pushes, 4 branches in 4 months
laktionov/Practical_RL
Dec 2022 - Dec 2022
A course in reinforcement learning in the wild
Contributions:2 pushes in 1 day
reinforcement-learningreinforcementwilddeep-reinforcement-learning
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