Summary
Alex Khromenkov is a Lead Data Scientist with a decade of experience building high-load, production-grade systems and recommendation models at scale. Based in Moscow, he transitioned from leading backend and game-server engineering teams to architecting neural recommender solutions at OZON, applying BERT4Rec, Multi-GPU training, FlashAttention and experimentation with transformer and PostLN variants. He combines deep systems engineering (C#, .NET, Kafka, Kubernetes, ClickHouse) with hands-on ML research and feature engineering (Spark, Airflow, CatBoost, PyTorch/Lightning), enabling reproducible, performant pipelines for personalization. Comfortable bridging research and product, he has shipped distributed, fault-tolerant microservices and led cross-functional teams in both gaming and hardware-startup contexts. A PhD-level researcher by training from the United Institute of Informatics Problems and an MIPT alumnus, he brings a rare mix of low-level systems rigor and practical ML innovation.
10 years of coding experience
17 years of employment as a software developer
Ph.D Student, Information Technologies, Ph.D Student, Information Technologies at United Institute of Informatics Problems at National Academy of Sciences of Belarus
MSc, Information Technologies, Radio Engineering and Cybernetics Dep., MSc, Information Technologies, Radio Engineering and Cybernetics Dep. at Moscow Institute of Physics and Technology (State University) (MIPT)
Russian, English