Marcos Carlomagno
Staff Software Engineer at Tether.io
Rosario, Santa Fe, Argentina
Summary
👤
Senior🎓
Top SchoolMarcos Carlomagno is a Fullstack Ethereum Developer with 10 years of software engineering experience, currently building at OpenZeppelin from Rosario, Argentina. He blends blockchain-native backend work with front-end UX sensibilities, having moved through specialist roles at ProtoFire and several full‑stack positions where he delivered end-to-end web and mobile features. An active open-source contributor, Marcos authored a Flutter/TensorFlow Lite face recognition authentication project that highlights his interest in applied ML for user-facing security flows. His background in Systems Engineering informs a pragmatic approach to secure, auditable code and developer-friendly integrations. Colleagues know him for upgrading legacy projects smoothly (e.g., migrating to Flutter 2) and for striking a balance between protocol-level rigor and polished user interfaces.
11 years of coding experience
8 years of employment as a software developer
Systems Engineering, Systems Engineering at Universidad Tecnológica Nacional
Stackoverflow
1,651reputation
52kreached
2answers
1question
dart
top-5%
flutter
top-5%
Github Skills (10)
computer-vision10
machine-learning10
artificial-intelligence10
flutter-game10
dart10
flutter-apps10
flutter10
user-interface9
flutter-web6
emoji6
Programming languages (11)
Github contributions (5)
MCarlomagno/FaceRecognitionAuth
Sep 2020 - May 2022
😀🤳 Simple face recognition authentication (Sign up + Sign in) written in Flutter using Tensorflow Lite and Firebase ML vision library.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:1 release, 2 reviews, 48 commits in 1 year 8 months
Contributions summary:Marcos primarily contributed to the UI and feature enhancements, with an emphasis on the user authentication flow for a face recognition system. Their work included adding code comments and structure to the project. This involved modifications to the camera services, user interface elements, and implementing user authentication forms, while also upgrading to Flutter version 2.
authenticationface-recognitionfirebaseflutterml-vision
MCarlomagno/FlutterMobilenet
Aug 2020 - May 2021
🦾🤖 Mobilenet model implementation for image classification using the tflite library, a Flutter plugin for accessing TensorFlow Lite API.
Contributions:31 commits, 16 PRs, 25 pushes in 8 months
flutter-pluginimage-classificationmobilenettensorflow-litetflite
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