Summary
Sergey Shirobokov is a Senior Research Engineer with nine years of experience applying machine learning to large-scale systems, currently working at Google DeepMind after roles at ShareChat, Twitter, CERN and Amazon. He holds a PhD from Imperial College London focused on differentiable generative surrogate models for experiment hyperparameter optimization and is a Yandex School of Data Analysis alumnus with deep expertise in Big Data and ML. Sergey has shipped production improvements—from tweet candidate generation and ads multi-task models at Twitter to uncertainty-aware recommendation research at Amazon—and co-authored fast, scalable graph link-prediction work recognized at ICLR. Comfortable straddling research and engineering, he combines physics-rooted problem-solving with pragmatic implementations in Python, PyTorch and TensorFlow to deliver both state-of-the-art papers and measurable product gains. An under-the-radar strength is his track record of turning complex experimental needs (CERN, SHiP) into efficient surrogate models that accelerate real-world optimization.
9 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Algorithms for High Energy Physics, Doctor of Philosophy - PhD Algorithms for High Energy Physics at Imperial College London
Master's degree Computer Science, Master's degree Computer Science at Higher School of Economics
Master of Science (MSc) Data Analysis / Machine Learning, Master of Science (MSc) Data Analysis / Machine Learning at Yandex School of Data Analysis
Lomonosov Moscow State University
Русский, English, German