Tammam Bettaieb@Tammam_bt

About me

I don't just pull high-level frameworks off the shelf; I prefer to master the math, logic, and architecture underneath them. I am a Computer Science Engineering student at the National School of Computer Science (ENSI), focused on building reliable, low-level, and scalable technology from first principles. Whether it is writing machine learning algorithms from scratch using raw mathematical concepts or designing real-time control loops for autonomous robots, I thrive where software meets complex system logic. Here is a snapshot of what I engineer: - Machine Learning & Infrastructure: Developed and published 'Axiom-ml' on PyPI—a lightweight ML and deep learning library built entirely from scratch using NumPy. My goal is bridging the gap between foundational ML theory and production-grade AI Infrastructure (MLOps). - Robotics & Embedded Systems: Designing navigation architectures, hardware-software integration, and PID/MPC controllers for the Eurobot competition, leveraging ROS2 Jazzy, STM32, and Raspberry Pi 5. - Backend & Automation: Engineering robust backend systems, RESTful APIs, and complex data automation workflows (ETL scraping pipelines, persistent-memory chatbots, and database normalization). I love putting my skills to the test under pressure. Recently, my teams took 1st Place at DataLeaders 2.0 and 2nd Place at Roboday 4.0. Let’s connect if you want to discuss MLOps, AI infrastructure, robotics, or backend architecture!

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