Eugene Trapeznikov is a senior machine learning engineer with 16 years of software development experience, currently applying ML expertise to personalization and recommendation problems at Etsy. He has led production ML efforts at Amazon, migrating pipelines to Airflow, introducing a feature store, and optimizing large-scale Hadoop/Spark jobs on AWS EMR. Earlier work on Alexa combined on-device speech recognition, privacy-preserving federated learning, and cross-team hardware integrations, reflecting a rare blend of mobile, embedded, and ML systems experience. Eugene’s background in mobile app architecture and CI/CD improvements across startups demonstrates strong product instincts and operational rigor alongside research-grade ML skills. He holds advanced training from Stanford’s AI program and dual degrees from the Higher School of Economics, and is known for translating complex experiments into automated, reproducible MLOps workflows. Colleagues would note his practical focus on scalable deployment and his habit of improving processes as well as models.
15 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Computer Science, Programming, Data Bases, Management, Economy, Business Modeling, Bachelor's degree, Computer Science, Programming, Data Bases, Management, Economy, Business Modeling at Higher School of Economics
Artificial Intelligence Professional Program, Artificial Intelligence Professional Program at Stanford University
Contributions:2 PRs, 2 pushes, 3 branches in 1 day
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Eugene Trapeznikov - Sr. Machine Learning Engineer at Etsy