Maria Lomeli
Software Engineer at Meta
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolMaria Lomeli is a London-based software and research engineer with eight years’ experience translating ML research into production at Meta and Babylon Health. She holds a PhD in Machine Learning from UCL and combines a quantitative foundation in actuarial science and mathematical sciences with hands-on MLOps and data engineering. Her open-source contributions include work on the widely used FAISS library—implementing and deploying an offline IVF big-batch search framework with GPU acceleration and dimensionality reduction to scale vector similarity search. Maria excels at bridging rigorous evaluation and scalable deployment, turning experimental NLP/ML models into optimized services.
8 years of coding experience
8 years of employment as a software developer
Universidad Nacional Autónoma de México (UNAM)Bachelor's degree, Actuarial Science, Bachelor's degree, Actuarial Science at Instituto Tecnológico Autónomo de MéxicoUniversity College London
Github Skills (9)
machine-learning10
faiss10
dimensionality-reduction10
python10
gpu-programming9
pytorch8
data-engineering8
ci-cd7
testing7
Programming languages (4)
Github contributions (5)
facebookresearch/faiss
Nov 2022 - Nov 2022
A library for efficient similarity search and clustering of dense vectors.
Role in this project:
MLOps Engineer & Data Engineer
MLOps Engineer & Data EngineerContributions:3 releases, 7 commits, 20 PRs in 6 days
Contributions summary:Maria primarily contributed to the development and deployment of the offline IVF framework, which leverages big batch search for efficient vector similarity search on large datasets. Their work involved integrating the framework with GPU-accelerated FAISS for significant performance gains. This included implementing and testing dimensional reduction techniques, demonstrating a focus on scalable and optimized machine learning solutions. The user also worked on test and evaluation of the offline IVF framework.
k-meansvectorssimilarity-searchmachine-learningsimilarity
mlomeli1/faiss
Nov 2022 - Jan 2025
A library for efficient similarity search and clustering of dense vectors.
Contributions:28 pushes, 9 branches in 2 years 2 months
approximate-nearest-neighbor-searchk-meansvectorssimilarity-searchmachine-learning
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