Matt
Machine Learning Engineer at huggingface
Dublin, Dublin 1, Ireland
Summary
🤩
RockstarMatt is a Machine Learning Engineer based in Dublin with a decade of hands-on experience building and improving ML tooling and libraries. He contributes to high-profile open-source projects including Hugging Face, Keras, scikit-learn-contrib HDBSCAN, UMAP and transformers, where his work spans core algorithm tweaks, TensorFlow integration, and dataset-to-TF pipeline improvements. He has a track record of shipping pragmatic fixes—adding RaggedTensor support to Keras predict, introducing max_cluster_size to HDBSCAN, and enhancing to_tf_dataset for better padding and multi-label support—that improve real-world model usability. Comfortable in both Python and Cython, he focuses on robust testing, performance-aware changes, and edge-case handling such as sparse precomputed distances and variable-length inputs. Colleagues would describe him as the engineer who bridges research-grade algorithms and production-ready data pipelines within major ML ecosystems.
10 years of coding experience
Github Skills (31)
transformers10
sparse10
pytorch10
data-pipelines10
python10
imap10
testing10
scikit10
machine-learning10
hdbscan10
machine-learning-algorithms10
numpy10
datasets10
keras10
huggingface-transformers10
Programming languages (9)
Github contributions (5)
huggingface/transformers
Mar 2019 - Jan 2023
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Role in this project:
ML Engineer
ML EngineerContributions:1321 reviews, 206 commits, 830 PRs in 3 years 10 months
Contributions summary:Matt's contributions center around the implementation of a new LM finetuning example, introducing and modifying files related to a pregenerated dataset for language model fine-tuning using the Hugging Face Transformers library. The code includes the definition of a custom dataset class, feature conversion, and training loop integration with the `BertForPreTraining` model. The user also addressed code style issues and improved test setup, indicating a focus on creating a functional and usable example.
pythonbertspeech-recognitionstate-of-the-artflax
huggingface/notebooks
Sep 2021 - Jan 2023
Notebooks using the Hugging Face libraries 🤗
Role in this project:ML Engineer
ML EngineerContributions:18 reviews, 42 commits, 28 PRs in 1 year 4 months
Contributions summary:Matt appears to be focused on developing and improving TensorFlow-based notebooks for training and utilizing Hugging Face libraries. Their contributions center on creating and updating language modeling notebooks, including those for causal language modeling, masked language modeling, and language modeling from scratch, all implemented with TensorFlow. The user also addressed mandatory data collator requirements and fixed typos, showcasing a focus on code functionality and usability within the context of Hugging Face's library ecosystem.
nlpdeep-learningmachine-learninghugging-facenotebooks
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