Machine Learning Researcher
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Skills in Machine Learning/Deep Learning. Research in Computer Vision, Video processing, Anomaly detection.
AGH University of Krakow
Habilitation, Design of low-latency architectures for machine learning algorithms
April 1, 2021 – Present
AGH University of Krakow
PhD, High-Performance Reconfigurable Computing
January 1, 2005 – January 1, 2010
AGH University of Krakow
M.Sc., Electronics and Telecommunication
January 1, 1999 – January 1, 2005
NIBIO Norwegian Institute of Bioeconomy Research
Machine Learning Researcher
September 1, 2022 – Present
Norway · On-site
Computer Vision Center
Machine Learning Researcher
May 1, 2021 – August 1, 2022
Barcelona, Catalonia, Spain · On-site
AGH University of Krakow
Assistant Professor
February 1, 2017 – August 1, 2022
Cracow, Małopolskie, Poland · Hybrid
Cadence Design Systems
Deep Learning Research Engineer
February 1, 2017 – September 1, 2020
San Jose, California, United States · Remote
CERN
Deep Learning Research Engineer
February 1, 2016 – January 1, 2017
Geneva Area, Switzerland · On-site
AGH University of Krakow
Assistant Professor
October 1, 2012 – January 1, 2016
Cracow, Małopolskie, Poland · On-site
Norwegian University of Science and Technology (NTNU)
Postdoctoral Research Fellow
October 1, 2011 – September 1, 2012
Norway, Trondheim · On-site
AGH University of Krakow
Assistant Professor
May 1, 2010 – September 1, 2011
Cracow, Małopolskie, Poland · On-site
AGH University of Krakow
Teaching Assistant
December 1, 2007 – April 1, 2010
Cracow, Małopolskie, Poland · On-site
Introduction to Self-Driving Cars
Coursera
June 24, 2026 – Present
Cambridge English: Advanced (CAE)
Cambridge English
June 24, 2026 – Present
Advanced LiDAR Data Processing and Object Detection in Robotics
BlackBird
June 24, 2026 – Present
Robotics Essentials
Emeritus
June 24, 2026 – Present
MIT xPRO Robotics Essentials
Emeritus
June 24, 2026 – Present
Bayesian Methods for Machine Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong academic background with significant research experience across multiple institutions (NIBIO, CVC, CERN, AGH, NTNU). This indicates adaptability to diverse research environments. The focus on R&D roles aligns well with an ML Engineer position that often requires innovation and problem-solving. However, the lack of diverse industry projects outside of research settings might indicate a preference for academic or research-heavy environments, which may or may not align with a specific company culture. The candidate's experience is heavily skewed towards research, which is a good fit for an ML Engineer role, but the breadth of project types (e.g., product development, deployment at scale) is not explicitly detailed.
Soft Skills & Operational Fit
The candidate's extensive research background suggests strong analytical and problem-solving skills. Experience in academic roles (Assistant Professor, Teaching Assistant) implies good communication and mentoring abilities. However, the provided data does not offer direct insights into stress handling, team collaboration, or work attitude beyond the psychometric test score which is 0, indicating insufficient data for a proper assessment.