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AI @ Amazon Frontier AI & Robotics, Scout @ a16z speedrun | Ex Meta AI | VGG, University of Oxford
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Passionate about AI and Computer Vision. PhD from Oxford and Meta AI 🇬🇧 Engineering and Master's Degree in Computer Vision from École Polytechnique Paris 🇫🇷
University of Oxford
Doctor of Philosophy - PhD, Engineering Science
October 1, 2021 – October 1, 2024
École Polytechnique
Engineering and Master’s degree, Machine Learning and Computer Vision
January 1, 2017 – January 1, 2020
Novosibirsk State University (NSU)
Bachelor's degree, Mathematics and Computer Science
January 1, 2013 – January 1, 2017
Amazon
AI Research
October 1, 2025 – Present
London Area, United Kingdom
pixelwise.ai
Founder (Acquired by Amazon)
October 1, 2024 – October 1, 2025
London Area, United Kingdom · On-site
Facebook AI
AI Research
January 1, 2022 – October 1, 2024
Greater London, England, United Kingdom
Facebook AI Research (FAIR)
Research Intern
May 1, 2021 – September 1, 2021
Paris, Île-de-France, France
WANNA
Computer Vision Research Engineer
August 1, 2020 – December 1, 2021
Remote
Fujitsu Global
Machine Learning Engineering Intern
June 1, 2019 – August 1, 2019
Tokyo, Japan
Teleport Future Technologies, Inc.
Computer Vision Engineer
November 1, 2016 – December 1, 2017
Moscow, Moscow City, Russia
18th out of 935 (Top 2%): Lyft Motion Prediction for Autonomous Vehicles
September 1, 2020 – November 1, 2020
Achieved 18th place out of 935 participating teams in the “Lyft Motion Prediction for Autonomous Vehicles” competition on Kaggle, in which participants were asked to build models that reliably predict the movement of traffic agents around the AV, such as cars, cyclists, and pedestrians. Our final approach that combined data processing methods (Python) and advanced deep neural networks (PyTorch) allowed us to reach the top place on the leaderboard.
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across academia, startups, and large tech companies (Amazon, Facebook AI) demonstrates adaptability and a broad perspective. Their involvement in frontier AI research and general-purpose robotics aligns well with an innovative and ambitious culture. The success in a competitive environment like Kaggle and leading research projects indicates a drive for excellence and a proactive approach, which are strong indicators of cultural fit for a high-performing technical team.
Soft Skills & Operational Fit
The candidate's entrepreneurial background and leadership in research projects suggest strong problem-solving, innovation, and initiative. Their contributions to open-source projects (CoTracker with 4k+ stars) indicate a collaborative spirit and ability to deliver impactful work. The descriptions of optimizing algorithms for mobile devices and achieving top Kaggle rankings demonstrate a results-oriented and efficient approach. However, without direct assessment data, specific soft skills like team collaboration or stress handling cannot be definitively evaluated.