Molka B
AI & QA Automation Engineer | AI Bias Audit& Web/App Testing
AI Bias Detection & Mitigation Tool for Hiring Models
My role: AI/ML Engineer & Fairness Auditor
Project description:
AI Bias Detection and Mitigation Framework for Recruitment Systems.
Built a complete, production-ready tool that:
Detects gender, race, and age bias in hiring ML models
Uses industry-standard fairness metrics (Disparate Impact, Demographic Parity, Equal Opportunity)
Applies Reweighing mitigation (AIF360) → improves fairness while keeping accuracy loss < 2%
Includes interactive Gradio demo for live testing
Full business impact section + compliance notes (EEOC 4/5th rule, GDPR, EU AI Act)
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E-commerce Automation Framework
My role : Test Automation Engineer (UI & API)
Project description:
Designed and developed a comprehensive automated testing framework for an e-commerce website. The framework covers UI automation using Selenium WebDriver and Pytest, alongside robust API testing to ensure backend reliability. It enables fast, repeatable test execution with detailed reporting to quickly identify issues.
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88
QA Test Summary Report – SaaS Platform Release
My role : QA Engineer / Test Lead
Project description:
Executed risk-based QA testing for a SaaS platform (v1.0.1), focusing on Authentication, RBAC, and User Dashboard. Identified critical security vulnerabilities, session integrity failures, and major functional defects. Delivered a professional test summary report with defect metrics, exit criteria validation, and actionable recommendations. Ensured the client had a clear release decision and mitigation plan, improving software reliability and compliance.
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AI-Powered QA Automation Suite
My role: Senior QA Automation Engineer (Lead)
Project description:
AI-Powered QA Test Case Generator & Execution Dashboard is a comprehensive, enterprise-level quality assurance solution designed to bridge the gap between AI-driven test generation and robust execution reporting. The suite provides a full-cycle automation workflow: from creating test cases using GPT-4 from natural language user stories to executing them across API and UI layers, finishing with high-impact business metric analysis.
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