Munaf Qazi
Director Of ML Engineering at Munich Re
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolMunaf Qazi is a Director of ML Engineering with nine years of experience building production-grade MLOps platforms and applied ML solutions in highly regulated industries. He led the design and deployment of an IAMD GitOps-based platform that cut model deployment times by 95% and engineered batch scoring that reduced run times from eight hours to four minutes. Equally comfortable in research and product, he published an open-source data-cleaning library (openclean) at VLDB and improved DARPA-backed web crawler performance at NYU. Munaf blends technical leadership with compliance and risk-aware engineering—implementing blue-green releases, model observability, and audit-ready controls across multi-geo tenants. He mentors early researchers, presents at conferences like PyData, and has a curious streak for practical prototypes from VR therapy to blockchain smart contracts. Based in New York, he’s as likely to recommend the best local ice cream as he is to design an experiment for automated underwriting.
9 years of coding experience
8 years of employment as a software developer
Bachelor of Science (BS) Electrical Engineering, Bachelor of Science (BS) Electrical Engineering at Lahore University of Management SciencesMaster of Science (MS) Computer Science, Master of Science (MS) Computer Science at New York University
French, Urdu, English
Github Skills (8)
crawler10
javas10
web-crawler10
webscraper10
webscraping10
java10
crawling10
documentation9
Programming languages (6)
Github contributions (5)
VIDA-NYU/ache
Jun 2017 - Jan 2019
ACHE is a web crawler for domain-specific search.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:20 commits, 20 PRs, 3 pushes in 1 year 7 months
Contributions summary:Munaf primarily contributed to improving the ACHE web crawler by adding functionality to handle non-HTML pages, which indicates efforts to broaden the crawler's data ingestion capabilities. Further enhancements were made to the documentation, improving user understanding and facilitating easier use of the tool. Additional changes were introduced to the HTTP fetcher using OkHTTP3, enabling the configuration of proxy settings and timeouts, suggesting a focus on improving the crawler's robustness and configuration flexibility.
focused-crawlerweb-crawlerspiderweb-searchsearch-engine
VIDA-NYU/openclean-pattern
Nov 2020 - Apr 2021
Pattern identifier and anomaly detector
Contributions:1 release, 79 commits, 4 PRs in 5 months
anomalyidentifiermachine-learningdetectorpattern
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