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Machine Learning Engineer, PhD
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Experienced machine learning engineer specializing in computer vision and deep learning for real-world applications. Proven track record in developing efficient mobile ML models for image, radar, 3D vision. Expertise in neural network architecture optimization and signal processing. Passionate about applying AI to solve complex challenges in robotics, healthcare, and consumer electronics.
Poznan University of Technology
Doctor of Philosophy - PhD
January 1, 2014 – January 1, 2020
Poznan University of Technology
Master's degree, Mechanical Engineering
January 1, 2009 – January 1, 2014
NVIDIA
Senior Deep Learning Engineer
October 1, 2024 – Present
Munich, Bavaria, Germany
Machine Learning Software Engineer via Mobica
August 1, 2020 – October 1, 2024
Mountain View, California, United States · On-site
Mobica
Senior Software Engineer
June 1, 2020 – October 1, 2024
FX-Tronik
Machine Learning Engineer
January 1, 2018 – April 1, 2020
Poznań, Wielkopolskie, Poland
StethoMe™
Machine Learning Engineer
March 1, 2017 – December 1, 2017
Poznań, Wielkopolskie, Poland
SnapRapid
Machine Learning Developer
September 1, 2016 – February 1, 2017
London Area, United Kingdom · Remote
Poznan University of Technology
Research Assistant
October 1, 2014 – July 1, 2021
Poznań, Wielkopolskie, Poland
Cultural Fit Analysis
The candidate has worked in diverse environments, from academic research to startups (StethoMe, SnapRapid, FX-Tronik) and large corporations (Google, NVIDIA). This breadth of experience suggests adaptability to different company cultures. The focus on cutting-edge ML applications aligns well with an innovative, research-driven culture. The lack of project details beyond job descriptions limits a deeper cultural fit analysis.
Soft Skills & Operational Fit
The candidate's resume descriptions highlight leadership, innovation, and problem-solving skills. Experience in diverse project environments (startups, large corporations, research) suggests adaptability. However, without psychometric or English test results, a comprehensive assessment of soft skills and operational fit is limited.