Suhaib Mujahid
Staff Machine Learning Engineer at Mozilla
Montreal, Quebec, Canada
Summary
🤩
Rockstar🎓
Top SchoolSuhaib Mujahid is a Staff Machine Learning Engineer at Mozilla with a decade of experience building production ML systems and back-end services. He holds a PhD in Software Engineering from Concordia and publishes research in top international venues, bridging academic rigor with industry impact. At Mozilla he has delivered reliable ML pipelines (bugbug) and backend improvements to large-scale projects such as Bugzilla and git2go, demonstrating comfort across model training, data engineering, and API/database work. Known for turning research into practical tools, he frequently contributes to open source and has a track record of improving developer-facing APIs and model robustness. Based in Montreal, he combines deep academic credentials (4.19/4.19 PhD GPA) with hands-on engineering that surfaces subtle reliability fixes developers rely on.
10 years of coding experience
16 years of employment as a software developer
Bachelor’s Degree, Information Systems, Bachelor’s Degree, Information Systems at Palestine Polytechnic UniversityDoctor of Philosophy - PhD, Software Engineering, 4.19/4.19, Doctor of Philosophy - PhD, Software Engineering, 4.19/4.19 at Concordia University
Github Skills (31)
api-rest10
git10
bugzilla10
debug10
libgit210
database-api10
python10
apidoc10
api-design10
restful-api10
data-engineering10
databases10
machine-learning10
perl10
ml10
Programming languages (16)
Github contributions (5)
mozilla/bugbug
Mar 2022 - Nov 2022
Platform for Machine Learning projects on Software Engineering
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 1321 reviews, 11 commits in 7 months
Contributions summary:Suhaib primarily contributed to the project by fixing bugs related to model training and data handling, along with refactoring some code. They improved the error messages for missing model names and updated versions of the bugbug commits database. Furthermore, the user made enhancements for the code analysis, handling none values from `rust-code-analysis` for the halstead metrics. This indicates a focus on model stability, data pipeline integrity, and the overall reliability of the machine-learning-focused project.
engineeringmachine-learningmachine-learning-projectsaideveloper-tools
libgit2/git2go
Jan 2020 - Feb 2021
Git to Go; bindings for libgit2. Like McDonald's but tastier.
Role in this project:Back-end Developer
Back-end DeveloperContributions:7 reviews, 16 commits, 12 PRs in 1 year 1 month
Contributions summary:Suhaib primarily contributed to the `git2go` project by implementing and refactoring Go code that provides bindings for the libgit2 library. Their work included fixing a nil signature issue, refactoring getter methods to align with Go idioms, and implementing new features related to setting environment variables for libgit2 and controlling hash verification. The user's changes touched upon various aspects of the library bindings, including remote operations, describe, merge, and more.
golanglibgit2gogit2gogit-gui
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