Gabriel Jablonski is a results-driven Chief Technology Officer with nine years of hands-on experience building full-stack systems and leading product engineering in Brazil. He has guided fintech and agtech platforms as CTO at FazendaNota and fazer.ai, blending product ownership with implementation of multi-agent LLM systems to solve real-world problems for farmers. Gabriel’s background spans frontend React work, Node.js APIs, and low-level video/audio tooling—he contributed VAAPI hardware-acceleration support to the MLT multimedia framework and added polished features to a popular React tooltip component. Comfortable alternating between C/C++ performance work and high-level system design, he’s known for shipping major project features and consulting across domains like finance and telecom. Based in Minas Gerais and trained in Computer Engineering at UFU, he combines pragmatic engineering discipline with a taste for optimizing multimedia and ML-infused workflows.
9 years of coding experience
4 years of employment as a software developer
BSc in Engineering, Computer Engineering, BSc in Engineering, Computer Engineering at Federal University of Uberlândia - UFU
Contributions:46 releases, 104 reviews, 89 commits in 1 month
Contributions summary:Gabriel primarily contributed to the development of the React tooltip component, focusing on new features and enhancements. They implemented a `positionStrategy` prop, added a `noArrow` option, and introduced a `clickable` prop to the tooltip. Additionally, the user improved the rendering of tooltip content, corrected data attribute handling, and addressed various bugs, ensuring proper functionality and user interaction with the component.
Contributions:7 reviews, 26 commits, 1 PR in 1 month
Contributions summary:Gabriel's primary contribution focused on adding VAAPI (Video Acceleration API) support to the MLT Multimedia Framework. This involved modifying the `producer_avformat.c` file to incorporate hardware-accelerated video decoding using VAAPI. The changes include adding necessary headers, implementing functions to handle hardware device context, and modifying image processing to utilize hardware acceleration. These improvements likely aim to enhance video processing performance.
c-plus-plusmultimediavideofrei0rvaapi
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Gabriel Jablonski - Chief Technology Officer at fazer.ai