Suraj Parmar
Machine Learning Engineer at Maisa
Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolSuraj Parmar is a Machine Learning Engineer with a decade of experience building production-grade AI systems where reliability and security matter. Based in Toronto, he has delivered deployable solutions across healthcare, real estate, and finance—ranging from sepsis prediction models and synthetic clinical language datasets to ensemble valuation APIs and Numerai signal models. He specializes in agentic workflows, LLM deployment (including air-gapped, secure RAG systems), and production ML reliability, pairing deep learning and GBDT approaches to maximize real-world performance. His open-source contributions include model engineering and feature work for the popular Numerai example scripts, demonstrating practical expertise in feature engineering and model robustness. Suraj holds an MSc in Artificial Intelligence with top grades and has a track record of turning research ideas into secure, maintainable production services. Colleagues describe him as pragmatic and detail-oriented, with a knack for adapting state-of-the-art methods to operational constraints.
10 years of coding experience
3 years of employment as a software developer
Bachelor of Engineering (B.E.), Computer Science, 8.78/10, Bachelor of Engineering (B.E.), Computer Science, 8.78/10 at Faculty of Engineering Technology and Research, SuratMaster of Science - MSc, Artificial Intelligence, 9.2/10, Master of Science - MSc, Artificial Intelligence, 9.2/10 at University of Windsor
Github Skills (12)
scikit10
pandas10
machine-learning10
feature-engineering10
python10
data-science10
numpy10
scikit-learn10
api8
time-series8
apim8
data-analysis8
Programming languages (7)
Github contributions (5)
numerai/example-scripts
Jan 2021 - May 2021
A collection of scripts and notebooks to help you get started quickly.
Role in this project:
Data Scientist
Data ScientistContributions:5 reviews, 12 commits, 7 PRs in 4 months
Contributions summary:Suraj primarily contributed to the development of machine learning models within the Numerai signals framework. They focused on data loading, feature engineering, and model training using Quandl and AlphaVantage datasets. Key contributions include creating and integrating custom features such as RSI calculations, and quintile-based features, and implementing a GradientBoostingRegressor model for prediction. The user also addressed KeyErrors in the data loading pipeline and refactored the code by moving parts of the code around.
pythonsciencenumeraidata-sciencemachine-learning
uuazed/awesome-numerai
Jul 2021 - Nov 2022
A curated list of awesome numerai libraries, tutorials and other resources.
Contributions:3 commits, 3 PRs in 1 year 3 months
numerai
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