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Machine Learning Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Science Center
Data Mining
January 1, 2014 – January 1, 2016
Saint-Petersburg State Universiry
Master of Science (M.S.), Physics
January 1, 2013 – January 1, 2015
Saint-Petersburg State University
Bachelor of Science (B.S.), Physics
January 1, 2009 – January 1, 2013
Causaly
Staff Machine Learning Engineer
February 1, 2024 – Present
Greater London, England, United Kingdom · Remote
Meta
Senior Software Engineer
April 1, 2022 – August 1, 2023
Greater London, England, United Kingdom
Meta
Senior Software Engineer
March 1, 2021 – April 1, 2022
Greater London, England, United Kingdom
Meta
Software Engineer
February 1, 2018 – March 1, 2021
Greater London, England, United Kingdom
Yandex
Machine Learning Engineer
October 1, 2016 – January 1, 2018
Moscow, Moscow City, Russia
Segmento / RuTarget
Data Scientist
February 1, 2016 – October 1, 2016
St Petersburg, St Petersburg City, Russia
Aintsys: Automated Intelligence Systems
Quantitative Researcher
July 1, 2015 – February 1, 2016
St Petersburg, St Petersburg City, Russia
EFA Medica
Software Engineer
November 1, 2012 – July 1, 2015
St Petersburg, St Petersburg City, Russia
Kaggle Facebook V: Predicting Check Ins
May 1, 2016 – July 1, 2016
- Result: 8th / 1212, Top 1%. The goal of this competition was to predict which place a person would like to check in to. For the purposes of this competition, Facebook created an artificial world consisting of more than 100,000 places located in a 10 km by 10 km square.
Artificial Intelligence (Berkeley)
edX
June 24, 2026 – Present
Autonomous Naviration for Flying Robots (Technical University of Munich)
edX
June 24, 2026 – Present
Autonomous Mobile Robots (ETH Zurich)
edX
June 24, 2026 – Present
Cyber-Physical Systems (Berkeley)
edX
June 24, 2026 – Present
Embedded Systems - Shape the World (University of Texas at Austin)
edX
June 24, 2026 – Present
Introduction to Computational Thinking and Data Science (MIT)
edX
June 24, 2026 – Present
Introduction to Computer Science and Programming (MIT)
edX
June 24, 2026 – Present
Machine Learning (Stanford University)
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong background in Machine Learning and Data Science, with significant experience at major tech companies like Meta and Yandex. While the target role is 'Backend Engineer', the candidate's experience is heavily skewed towards ML Engineering. This suggests a potential fit for backend roles that are ML-intensive or require strong data processing and model integration. However, if the 'Backend Engineer' role is purely focused on traditional backend development (e.g., API design, database management, core business logic without heavy ML components), there might be a gap in direct experience. The project diversity is limited to one Kaggle competition, and the listed certifications are primarily ML/AI/Embedded Systems focused, reinforcing the ML specialization. The transition from Staff ML Engineer to a general Backend Engineer role would need further exploration to ensure alignment with core backend responsibilities.
Soft Skills & Operational Fit
The candidate's experience at Meta, a large tech company, suggests familiarity with structured development processes, collaboration, and potentially handling large-scale systems. The descriptions of expanding detection across multiple apps with the same team size indicate efficiency and strategic thinking. However, without direct assessment data, specific soft skills like communication clarity, stress handling, or team collaboration cannot be definitively evaluated.