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Computer Vision Engineer
Armed with deep learning expertise and a keen eye for computer vision, I'm in the business of leveraging image and video data to train production grade predictive and generative models. The following are a few of my technical competences listed as keywords: object detection, semantic segmentation, instance segmentation, scene understanding, image classification, GANs (generative adversarial networks), gaussian splatting, diffusion models, video diffusion, flow matching. And for the (not so smart) search engines: AI engineer, deep learning engineer, computer vision engineer, neural networks, artificial intelligence When I’m not programming and banging my head on a new problem you’ll find me sipping some coffee, trying a new restaurant or at the local gym
KTH Royal Institute of Technology
M.Sc., Computer Science
N/A – Present
Eindhoven University of Technology
M.Sc., Computer Science
N/A – Present
Università di Trento
Bachelor's degree, Computer Science
N/A – Present
EIT Digital Alumni
Master of Science (MSc), Data Science + Innovation and Entrepreneurship Minor
N/A – Present
Humanoid
Senior Deep Learning Engineer
February 1, 2026 – Present
London Area, United Kingdom · On-site
Meta
Computer Vision Engineer
December 1, 2024 – January 1, 2026
Zurich, Switzerland · Remote
Meta
Computer Vision Engineer
August 1, 2022 – February 1, 2024
Zurich, Switzerland · On-site
dentalXrai
Computer Vision Engineer
February 1, 2021 – August 1, 2022
Remote
Shell
Computer Vision Engineer
January 1, 2019 – June 1, 2020
Amsterdam Area, Netherlands · On-site
Ericsson
Data Scientist
March 1, 2018 – December 1, 2018
Stockholm, Sweden
Mapscape B.V.
Junior Software Engineer
August 1, 2017 – February 1, 2018
Eindhoven Area, Netherlands
Università di Trento
Guest Researcher
October 1, 2015 – February 1, 2016
Trento Area, Italy
Cultural Fit Analysis
The candidate has worked in diverse environments, including large corporations (Meta, Shell, Ericsson), startups (Humanoid, dentalXrai), and academic research. This breadth suggests adaptability. However, the descriptions of projects are very brief, limiting the ability to assess collaboration styles or specific cultural contributions. The target role of ML Engineer aligns well with the candidate's career trajectory in Computer Vision and Deep Learning.
Soft Skills & Operational Fit
The candidate's resume descriptions are concise, making it difficult to assess soft skills or operational fit beyond the technical roles. The psychometric test results are not provided, which would typically inform this area.