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Senior Software Engineer at Google
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
An experienced professional interested in the fields of Computer Vision, Natural Language Processing and Data Science.
Stanford Continuing Studies
Organizational Communication, General
April 1, 2026 – May 1, 2026
Higher School of Economics
Master of Science - MS, Data Science
January 1, 2017 – January 1, 2019
Yandex School of Data Analysis
Master of Science - MS, Data Science
January 1, 2015 – January 1, 2019
Irkutsk State University
Bachelor of Science - BS, Applied Mathematics & Computer Science
January 1, 2014 – January 1, 2017
Stony Brook University
Bachelor of Science - BS, Applied Mathematics & Computer Science
January 1, 2013 – January 1, 2014
Senior Software Engineer
April 1, 2026 – Present
Software Engineer
December 1, 2025 – April 1, 2026
Software Engineer
October 1, 2022 – December 1, 2025
Yandex
Senior Software Engineer / Analyst
August 1, 2020 – August 1, 2022
Moscow, Moscow City, Russia
Luka
Senior Machine Learning Engineer
July 1, 2018 – September 1, 2020
Moscow, Moscow City, Russia
Yandex
Deep Learning Engineer
October 1, 2017 – June 1, 2018
Moscow, Moscow City, Russia
source{d}
Machine Learning Intern
July 1, 2017 – September 1, 2017
Greater Madrid Metropolitan Area
Yandex
Computer Vision Senior Intern
December 1, 2016 – March 1, 2017
Moscow, Moscow City, Russia
Yandex
Computer Vision Intern
June 1, 2016 – September 1, 2016
Moscow
Linio México
Computer Vision Intern
December 1, 2015 – February 1, 2016
Intel Corporation
Software Engineer Intern
July 1, 2015 – August 1, 2015
Novosibirsk, Russia
Python Test
Mail.ru Group
June 24, 2026 – Present
The Data Scientist’s Toolbox
Coursera
June 24, 2026 – Present
Kaggle R Tutorial on Machine Learning
DataCamp
June 24, 2026 – Present
edX Honor Code Certificate for Introduction to Big Data with Apache Spark
edX
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
R Programming
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has worked in diverse environments, including large corporations (Google, Yandex, Intel) and startups (Luka, source{d}), indicating adaptability. The progression through various roles and departments (Antifraud, Core ML, AI Data) suggests a willingness to tackle different challenges. However, the project descriptions are minimal, making it hard to fully assess the breadth of their contributions and how they align with a 'Big Data Engineer' role, which typically involves more infrastructure and pipeline focus than pure ML model development. While there's an 'Introduction to Big Data with Apache Spark' certification, direct experience in large-scale data engineering is not explicitly detailed in the work history.
Soft Skills & Operational Fit
The candidate's resume indicates a strong technical trajectory and experience in complex AI/ML domains. However, without psychometric test results or interview data, it is difficult to assess soft skills such as logical reasoning, work attitude, stress handling, and team collaboration. The descriptions of past roles are brief, limiting insight into operational fit beyond technical contributions.