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Senior Machine Learning Engineer
For the past ten years, I've specialised in building and deploying complete, end-to-end machine learning solutions. As a Senior ML Engineer, my work spans the full stack, from architecting the infrastructure (migrating from the cloud to on-premise, optimising AWS costs) to implementing the data strategy (building custom tagging and augmentation pipelines). I enjoy solving complex technical challenges, whether that means containerising an entire workflow with Docker or optimising model inference speed with TensorRT. My focus is on delivering robust, scalable, and efficient ML systems that solve real-world problems. This passion for building things that work extends to my personal interests, where I enjoy the technical challenges of sailing and the craft of film photography. ⛵ 📸
Peter the Great St.Petersburg Polytechnic University
Master's degree, Computer Science
January 1, 2007 – January 1, 2014
Conntour (YC W25)
Machine Learning Engineer
August 1, 2025 – Present
Tel Aviv-Yafo, Tel Aviv District, Israel · Hybrid
FarmSee
Senior Machine Learning Engineer
November 1, 2021 – July 1, 2025
Kfar Saba, Israel · Hybrid
UVeye
Machine Learning Engineer / Applied Researcher
January 1, 2019 – October 1, 2021
Tel Aviv - Jaffa, Tel Aviv District, Israel · On-site
SAP
Senior Machine Learning Researcher
June 1, 2017 – December 1, 2018
Raanana, Israel
SAP
Machine Learning Researcher
July 1, 2015 – June 1, 2017
Raanana, Israel
SAP
Data Science Intern
February 1, 2015 – June 1, 2015
Raanana, Israel
SoftBalance
Marketing Analyst
June 1, 2013 – September 1, 2014
Saint Petersburg, Russian Federation · On-site
MAGNAT
Lead Analyst
January 1, 2013 – June 1, 2013
Saint Petersburg, Russian Federation · On-site
CCNA Routing and Switching
Cisco
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a consistent career progression in Machine Learning roles across multiple companies (SAP, UVeye, FarmSee, Conntour), indicating stability and commitment to the field. The diversity of projects (visual data analysis in farming, defect detection in vehicles, marketing analytics, financial risk prediction) suggests adaptability and a broad interest in applying ML to different domains. The target role of ML Engineer aligns perfectly with their extensive experience.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight problem-solving (optimizing AWS costs, handling unbalanced datasets), innovation (designing new pipelines, researching new features), and collaboration (mentoring, working on model development). These indicate a strong operational fit for a senior ML Engineer role.