Piero Molino
CEO & Co-founder at Studio Atelico
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolPiero Molino is a San Francisco–based AI founder and research engineer with 13 years of experience building production ML systems and developer tools. As CEO and co-founder of Studio Atelico and Predibase (where he previously served as CEO and now as Chief Scientific Officer), he blends product leadership with hands-on model and systems engineering. His research and industry roles span Stanford Hazy Research, Uber AI, and IBM, where he shipped real-world NLP, dialogue, and recommender solutions and founded the Ludwig low-code framework (6.5k+ stars) used for custom model building. An active open-source contributor, he has directly improved PPLM and Transformers text-generation examples and added dataset and feature support to Ludwig, showing care for reproducibility and usability. Trained with a PhD in Computer Science and a Stanford postdoc in AI, he pairs rigorous academic grounding with an operator’s instinct for scaling ML from prototype to product. Colleagues describe him as a pragmatic researcher who deliberately marries tooling improvements with applied deployment wins.
13 years of coding experience
13 years of employment as a software developer
Lisbon Machine learning Summer School LxMLS 2013Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at Università degli Studi di BariInnovaction LabMachine Learning Summer School 2012 KyotoEuropean Summer School in Information Retrieval ESSIR 2013Big DivePostDoc Artificial Intelligence, PostDoc Artificial Intelligence at Stanford University
Italian, English, French, Spanish
Github Skills (22)
pytorch10
hub10
language-model10
python10
machine-learning-models10
pre-trained-model10
machine-learning10
ml10
data-preprocessing10
deeplearning-ai10
deep-learning10
tensorflow10
natural-language-processing10
transformer10
nlp10
Programming languages (11)
Github contributions (5)
ludwig-ai/ludwig
Jan 2019 - Jan 2023
Low-code framework for building custom LLMs, neural networks, and other AI models
Role in this project:
ML Engineer
ML EngineerContributions:10 releases, 383 reviews, 1124 commits in 4 years 1 month
Contributions summary:Piero contributed to the development of the core Ludwig framework, with commits involving dependency management, image feature processing, and the implementation of new features like the TabNet combiner. The code changes centered around improving the codebase, including restructuring code, optimizing the performance of the system, and fixing reported issues. Additionally, the user worked on various enhancements like adding support for several datasets (e.g., MNIST, SST-2, Higgs Boson) to ensure dataset flexibility within the framework.
fairness-mlpythonframework-learningdeep-learning-frameworknatural-language-processing
uber-research/PPLM
Dec 2019 - Apr 2020
Plug and Play Language Model implementation. Allows to steer topic and attributes of GPT-2 models.
Role in this project:ML Engineer
ML EngineerContributions:1 review, 16 commits, 12 pushes in 4 months
Contributions summary:Piero primarily contributed to the codebase by implementing and refining features related to verbosity control and loss calculations within the PPLM model. They modified the `run_pplm.py` file to add verbosity levels and incorporate more detailed printing of loss values during the training process. Furthermore, the user addressed minor issues, likely improving code readability and potentially optimizing the training pipeline. The user also refactored and added a `run_pplm_discrim_train.py` to support BERT model.
nlppytorchtransformerslanguage-modelnatural-language-generation
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