Habeeb Shopeju
Senior Machine Learning Engineer - 3D Geometry at Autodesk Research
London, England, United Kingdom
Summary
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Senior🎓
Top SchoolHabeeb Shopeju is a Senior Machine Learning Engineer with nine years of experience building ML, IR, and production back-end systems, currently focused on 3D geometry at Autodesk Research. He has deep hands-on experience with retrieval-augmented generation, efficient inference for LLMs, and ML pipelines for finance and legal products from roles at Thomson Reuters and Primer.ai. An active contributor to Pyserini, he has improved evaluation, batching, and robustness in a widely used IR toolkit, reflecting a practical emphasis on reproducible search research. Habeeb blends research and engineering—designing data pipelines, extraction models, and MLOps tooling across cloud platforms—to move prototypes into production. Based in London, he pairs an electrical engineering background with applied NLP/vision work, and maintains an appetite for model efficiency and market-predictive ML that goes beyond typical search applications.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Engineering - BE, Electrical and Electronics Engineering, Second Class Upper, Bachelor of Engineering - BE, Electrical and Electronics Engineering, Second Class Upper at Federal University Of Agriculture, Abeokuta
Stackoverflow
419reputation
35kreached
15answers
0questions
Github Skills (13)
information-retrieval10
python10
testing9
error-handling9
lucene8
apidoc7
api7
shell6
curl6
repr6
firebase6
google-drive-api6
flask6
Programming languages (10)
Github contributions (5)
castorini/pyserini
Feb 2022 - May 2022
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 6 commits, 7 PRs in 3 months
Contributions summary:Habeeb made several contributions related to improving the Pyserini project. They addressed path issues in several scripts, modified the precision of DPR evaluation, and improved error messages for RM3 expansion. The user also refactored the test suite by changing setup and teardown methods to class versions and added bindings for batch document retrieval. Their work primarily focused on refining existing functionalities, improving error handling, and expanding the capabilities of the search and indexing features.
information-retrievalpython
HAKSOAT/DuFarms
May 2019 - Mar 2020
Implementation of a warehouse product tracking system
Contributions:35 commits, 3 pushes, 1 branch in 10 months
warehousetracking
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