Antonio Silletti
Bari, Apulia, Italy
Summary
👤
Senior🎓
Top SchoolAntonio Silletti is a Data Scientist specializing in artificial intelligence and large language models, bringing nine years of experience to his current role at IBM. He combines academic rigor from a Master's in Computer Science (AI) with hands-on research, having developed ClayRS, a Python framework to improve reproducibility in recommender systems at Università degli Studi di Bari. Antonio focuses on model fine-tuning, evaluation, and building reproducible ML pipelines, translating research practices into production-ready workflows. Based in Bari, Italy, he bridges research and industry, comfortable moving models from experimental settings to enterprise contexts. His background suggests a knack for tooling and frameworks that make complex experiments auditable and repeatable—an underrated but critical capability in modern AI teams.
9 years of coding experience
2 years of employment as a software developer
Master's degree, Computer Science - Artificial Intelligence, Master's degree, Computer Science - Artificial Intelligence at Università degli Studi di BariLiceo scientifico "E. Fermi"
English, Italian
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (20)
pylint10
python10
content-based-recommendation10
recommender-system10
continuous-integration8
lint8
linter8
devops7
static-code-analysis7
android7
huggingface6
wandb5
large-language-models5
pytorch5
docker5
Programming languages (2)
Github contributions (5)
swapUniba/ClayRS
Jan 2021 - Jan 2023
Complexly represent contents, build recommender systems, evaluate them. All in one place!
Contributions:12 releases, 772 commits, 40 PRs in 2 years
recommender-systemcontent-based-recommendationevaluation-metricspythongraph-based-recommendation
swapUniba/LaikaLLM
Oct 2023 - Aug 2024
A hub for training and evaluating LLMs, following the multitask paradigm, in the recommender system domain!
Contributions:4 releases, 9 PRs, 158 pushes in 10 months
recommender-systemlarge-language-modelsmultitask-learningreproducibilitywandb
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