Miguel Farrajota is a DataOps Engineer with a decade of experience building data-driven systems, distributed pipelines, and computer vision solutions from research prototypes to production. Based in the Greater Faro Area, he blends a PhD background in electronics and telecommunications with hands-on roles at Jungle and Feedzai, delivering scalable cloud and big-data workflows. His work spans full-stack development, deep learning for multi-person action recognition, and practical data engineering—bringing academic rigor to operational challenges. An active contributor to the Dask project’s documentation, he quietly improves developer experience in parallel computing ecosystems as well as production data reliability.
10 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Electric and Electronics Engineering, Bachelor's degree, Electric and Electronics Engineering at Universidade do Algarve
Contributions:57 PRs, 24 comments, 2 issues in 9 months
Contributions summary:Miguel's commits primarily focused on documentation updates within the Dask repository. Their contributions involved correcting grammar, punctuation, and naming conventions across multiple documentation files. These changes improved the clarity and readability of the documentation, encompassing various sections such as installation instructions, user interface descriptions, and internal design documentation.
A collection of popular datasets for deep learning.
Contributions:12 releases, 631 commits, 189 PRs in 5 years 7 months
pytorchluacross-languagepythonmatlab
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