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Senior Machine Learning Engineer @ Nebius | Token Factory
Driven Software and Machine Learning Engineer, demonstrating expertise in the full ML pipeline, from data engineering and model training to seamless integration with backend systems. Passionate about algorithms and system design, with solid experience in data engineering, and never shying away from DevOps work. Committed to high-quality coding standards and comfortable in leadership roles within startup environments. Actively seeking challenging opportunities in AI and Software Engineering to further apply and enhance my skillset.
Jagiellonian University
Master's Degree, Theoretical Computer Science
January 1, 2014 – January 1, 2018
Jagiellonian University
Bachelor's Degree, Theoretical Computer Science
January 1, 2011 – January 1, 2014
Nebius
Senior Machine Learning Engineer
March 1, 2026 – Present
Cracow, Małopolskie, Poland · Remote
Hopper
Senior Software Engineer (Machine Learning)
January 1, 2024 – March 1, 2026
Remote
bp
Data Engineer
June 1, 2023 – December 1, 2023
Remote
Ntropy
Machine Learning Engineer
October 1, 2021 – May 1, 2023
Remote
FLYR Labs (We're Hiring)
Senior Data Scientist
September 1, 2019 – September 1, 2021
Kraków Area, Poland · Hybrid
Nauto
Machine Learning Engineer
July 1, 2018 – September 1, 2019
Kraków Area, Poland · On-site
FORNAX.ai
Machine Learning Engineer
April 1, 2017 – July 1, 2018
Kraków Area, Poland · On-site
PredictionIO
Open Source Contributor
July 1, 2016 – November 1, 2016
SalesforceIQ
Software Engineering Intern
July 1, 2016 – October 1, 2016
Palo Alto · On-site
Software Engineering Intern
June 1, 2015 – September 1, 2015
Menlo Park · On-site
Sabre Corporation
Software Engineering Intern
July 1, 2013 – September 1, 2013
Cracow
Deep-Hedge MCCFR
March 1, 2020 – October 1, 2020
For my master's thesis I devised a novel algorithm called Deep-Hedge MCCFR for solving imperfect information games
Google Summer of Code - OTR encryption support for KDE Telepathy
May 1, 2014 – September 1, 2014
Successfully completed Google Summer of Code project for KDE. Created a D-Bus service responsible for Off-the-Record encryption for Telepathy and reflected its functionality in KDE Telepathy client.
Neural Networks for Machine Learning
Coursera Course Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has worked in diverse environments, from startups (Ntropy, FORNAX.ai) to larger corporations (Hopper, bp, FLYR Labs, Nauto, Facebook), and has experience with open-source contributions (PredictionIO, Google Summer of Code). This breadth suggests adaptability and a willingness to engage with different organizational cultures. The focus on cutting-edge ML problems and research (Master's thesis) indicates an innovative mindset. The contract-based roles might suggest a preference for project-based work or flexibility, which could be a fit depending on the target company's structure. The target role of ML Engineer aligns well with the candidate's career progression and stated expertise.
Soft Skills & Operational Fit
The candidate's resume highlights experience in designing and implementing complex systems, suggesting strong problem-solving and architectural thinking. Descriptions of establishing data warehouses and devising algorithms imply initiative and ownership. The Google Summer of Code project and Master's thesis indicate a capacity for independent research and development. However, without specific assessment data, direct evaluation of communication, teamwork, or stress handling is not possible.