Alexander Guschin is a machine learning engineer with more than a decade of experience spanning competitive ML, industry, and education. His career began as a student at a university in Moscow, where he discovered machine learning through Kaggle and rose to Grandmaster status, at one point ranking 5th globally. He then moved into industry: data analyst at Avito, data scientist on ride-sharing services at Yandex, and engineer at Mechanica AI, a startup bringing machine learning to industrial enterprises, where he mastered Docker, Kubernetes, and FastAPI on his way to becoming a full-stack ML engineer. He later joined Iterative.ai, a San Francisco startup building open source tools for machine learning engineers and data scientists.

Today Alexander leads data science and software engineering teams and contributes to open source ML tools. Teaching has become a central part of his work: he designs curricula around problems students care about, such as classifiers that detect bots in dialogues and machine learning system design projects scored on dual leaderboards for model quality and technical performance. He teaches teenagers as part of an international AI Olympiad, and his Coursera course on winning Kaggle competitions has been taken by more than 100,000 students.