Fiza Husain
Machine Learning Engineer at Stimuler
Bengaluru, Karnataka, India
Summary
🤩
Rockstar🎓
Top SchoolFiza Husain is a machine learning engineer with seven years of experience building end-to-end speech and applied ML systems, currently focused on production ML at Stimuler in Bengaluru. Her background spans research and industry roles—from AIOps and recommendation/GNN research at Microsoft to quantitative model work on securitized derivatives at Goldman Sachs—bridging rigorous research with production reliability. She has contributed to differential privacy and secure ML tooling in OpenMined’s PySyft ecosystem and published work on privacy-aware reinforcement learning at AAAI’22, reflecting a strong foundation in privacy-preserving ML and optimization. Comfortable across back-end engineering, test automation, and research, she brings a pragmatic emphasis on code quality and maintainability alongside modeling and evaluation. As an IIIT-H undergraduate researcher turned practitioner, she combines academic depth with production-focused delivery and a knack for translating complex ML research into reliable systems.
7 years of coding experience
2 years of employment as a software developer
Bachelor's degree Computer Science and Engineering, Bachelor's degree Computer Science and Engineering at International Institute of Information Technology Hyderabad (IIITH)
English, Hindi
Github Skills (4)
python10
testing10
pytest9
py9
Programming languages (7)
Github contributions (5)
OpenMined/PySyft
Aug 2021 - Jun 2022
Perform data science on data that remains in someone else's server
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:1 review, 97 commits, 8 PRs in 10 months
Contributions summary:Fiza primarily contributed to fixing linting errors within the codebase. This involved making changes to Python files, specifically within the test and core functionalities. These changes suggest a focus on code quality and potentially improving the project's maintainability. The user's work demonstrates proficiency in identifying and resolving code style issues to improve overall code health, and demonstrates the ability to work with existing testing frameworks.
pytorchcryptographyacquiringpythonscience
fiza11/tic_tac_toe
Jun 2019 - Jan 2020
A simple Tic-Tac-Toe game built on React.
Contributions:5 PRs, 10 pushes, 3 branches in 6 months
reacttoetacreactjstic
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