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Working from home
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Working from home
53 followers · 57 following

Achievements

Achievement: Pull Sharkx2Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Quickdraw

Achievements

Achievement: Pull Sharkx2Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Quickdraw

Highlights

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Diogo-Serra/README.md
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About me

Delivery leader with over a decade of experience scaling teams and high-level operations, now building technical depth in AI & software engineering. I work primarily in C, Python, and bash, with growing focus on AI, machine learning, LLMs and DevOps. I spend most of my time around computers, driven by curiosity about understanding how things really work.

Currently at 42 Lisbon, specializing in AI, Machine Learning, and LLM-based systems, with a growing focus on DevOps. Building hands-on expertise across model development, ML pipelines, and infrastructure automation, while strengthening core software engineering foundations in C, Python, and UNIX.
I'm a cat person. Into Souls games, Baldur's Gate, Path of Exile, survival games, and Magic: The Gathering.

portfolio

C Python Bash Linux Open-Source AI Machine Learning LLMs DevOps

Skills

C Python Bash HTML CSS Visual Basic Markdown

Nginx Git CMake Vim VS Code Docker

AI Machine Learning PyTorch Hugging Face

MySQL MongoDB

Linux macOS

GitHub Stats

Streak Top Languages

"You must gather your party before venturing forth"

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  1. 42_School 42_School Public

    42 School projects - C, Python, AI, Machine Learning, Bash, Git, Linux. Learning core programming fundamentals through hands-on, peer-reviewed projects.

    C 5

  2. 42_Piscine 42_Piscine Public

    A collection of C programming exercises and projects completed during the 42 Lisboa Piscine, covering core concepts like memory management, algorithms, and Unix fundamentals.

    C 5 1

  3. AI_Machine_Learning AI_Machine_Learning Public

    A collection of hands-on AI and machine learning projects exploring how models actually work: from LLM fundamentals (tokenization, attention, autoregressive generation) to applied systems.

    Makefile 1

  4. local-llm-env local-llm-env Public

    Reproducible environment for running open-weight language models locally, combining llama.cpp (inference) and opencode (agent harness) behind a small set of make targets.

    Makefile

  5. intentCast-mcp intentCast-mcp Public

    MCP server that turns natural language prompts into schema-valid function calls using a local small LLM (Qwen3-0.6B) with constrained decoding.

    Python 1

  6. codedex.io codedex.io Public

    CodΓ©dex Python exercises & solutions - variables, loops, conditionals, and more, part of a broader hands-on series covering GitHub Copilot, the command line, and Git & GitHub.

    Python 2