Lev Fedorov is a software engineer at Amazon specialising in large-scale recommender systems and ranking for consumer products. He has worked on short-video feeds, image search and discovery systems serving millions of users, owning everything from candidate generation and ranking models to experimentation frameworks and observability. Lev has led migrations from classic k-NN + matrix factorisation stacks to more interpretable architectures with per-request traces and dashboards that help product and trust & safety teams understand “why this item was shown”. He enjoys sharing real-world lessons on recommender systems, feedback loops and responsible AI with data science communities.
