Jorge Cardona is a Senior Machine Learning Engineer based in Berlin with 16 years of experience blending deep mathematical research and hands-on software engineering. He holds a PhD in Mathematics and transitioned from postdoctoral work on stochastic analysis and heterogeneous diffusion to applied ML roles where he redesigned transformer-based models for NLP and now builds safety-focused ML at Beams Safety AI. Jorge’s background spans backend systems, IoT platform co-founding, security and performance testing, and scalable cloud architectures—skills he pairs with rigorous theoretical thinking. An active open-source contributor, he improved Guake’s backend behavior and introduced per-directory terminal title configuration and a cached file manager, reflecting a knack for practical tooling improvements. Known for tackling technically subtle problems, he combines probabilistic insight with production-grade engineering to deliver reliable, customer-facing solutions.
16 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy - PhD, Mathematics, Doctor of Philosophy - PhD, Mathematics at University of Miami
Bachelor, Electrical Engineering, Bachelor, Electrical Engineering at Universidad Pontificia Bolivariana
Contributions:6 reviews, 7 commits, 2 PRs in 1 year 11 months
Contributions summary:Jorge primarily contributed to the Guake terminal's back-end functionality, enhancing its behavior and features. They modified the application's configuration loading mechanism, preventing unnecessary reloads and introducing a new setting to control the loading of `.guake.yml` files. Furthermore, they introduced a proof of concept for dynamically setting terminal titles using a per-directory configuration file. Finally, the user created and implemented a file manager with caching capabilities.
Contributions:36 pushes, 3 branches in 1 year 11 months
gnome-shell-extensionlinuxgnomedrop-downterminal
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