Alberto De Paola Terzaghi
Engineer at Meta
United States
Summary
🤩
Rockstar🎓
Top SchoolAlberto De Paola Terzaghi is an experienced engineer with 12 years building enterprise web applications and driving integrations across Java, Python, C#, and PHP stacks. Currently at Meta, he works with Llama models to help companies adopt LLMs and contributes to high-profile open-source efforts like the llama-cookbook, where he improved fine-tuning metrics and monitoring for multi-GPU runs. A pragmatic generalist, he spans the full software lifecycle—from business analysis and BPM-driven process design to sysadmin and DevOps—and has led partner engineering and global launch efforts at Facebook. He favors lean, fast tooling and has a track record of creating robust automation for workflow engines and mobile/IoT supply-chain solutions. With a background that blends academic teaching, startup founding, and enterprise leadership, he brings both technical depth and product-focused pragmatism to complex integrations.
12 years of coding experience
11 years of employment as a software developer
Nanodegree, Information Technology, Full Stack Web Developer, Nanodegree, Information Technology, Full Stack Web Developer at UdacityBachelor in Social Science, Social Sciences, Bachelor in Social Science, Social Sciences at Federal University of Rio Grande do SulLicenciatura em Computação, Information Technology, Pedagogy, E-Learning, Licenciatura em Computação, Information Technology, Pedagogy, E-Learning at Universidade La SalleLic, Historia, Lic, Historia at University of Buenos Aires
Spanish, Portuguese, English, Italian
Stackoverflow
1,160reputation
233kreached
6answers
0questions
64-bit
top-5%
compact-framework
top-5%
uri
top-5%
Github Skills (19)
python10
llama10
machine-learning10
fine-tuning10
matplotlib9
compact-framework9
json9
pytorch9
uri9
64-bit9
oracle6
bubble-sort6
rxtx6
httpwebrequest6
windows6
Programming languages (4)
Github contributions (5)
meta-llama/llama-cookbook
Sep 2023 - Mar 2025
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
Role in this project:
ML Engineer
ML EngineerContributions:47 reviews, 30 PRs, 10 pushes in 1 year 5 months
Contributions summary:Alberto implemented functionality to save and plot fine-tuning metrics, including training and validation loss and perplexity, in a JSON format. This involved modifications to the training utilities to record these metrics and a new script for plotting them, indicating a focus on monitoring and analyzing the performance of Llama models during fine-tuning. Furthermore, the user added the rank to the metrics filename to distinguish the run from each GPU, as well as updating the prompt format for a Llama Guard model, suggesting a focus on model development and evaluation.
aifinetuninglangchainllamallama2
albertodepaola/llama-recipes
Sep 2023 - Sep 2024
Examples and recipes for Llama 2 model
Contributions:84 pushes, 21 branches in 1 year
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