Summary
Alexander Kolesov is a Senior AI & Machine Learning Engineer with eight years of applied experience turning research-grade models into production-grade systems across LLMs, RL, CV, NLP and time-series. He combines low-level systems intuition (C/C++, CUDA) with rapid prototyping in PyTorch/Hugging Face and multi-GPU RAPIDS pipelines to cut ETL and training latency dramatically for TB-scale data. Recent projects include LLM-driven market-signal pipelines, a fault-tolerant real-time trading bot on Binance testnet, and serverless CV at scale, while his MLOps practice enforces retraining, monitoring, SLI/SLOs and model governance. Trained academically in intelligent systems and candidate-level computer science, he also pursues optimal transport, Bayesian deep learning and generative models on GitHub, reflecting a research-to-production mindset. Multilingual (EN/DE/RU) and open to relocation, he focuses on responsible AI, explainability and regulated-domain governance as practical parts of deployment.
8 years of coding experience
8 years of employment as a software developer
Master's degree, Intelligent Systems, Master's degree, Intelligent Systems at Universitat Jaume I
Moscow State Technological University "Stankin"
English, German, Russian, Spanish