I build practical tools and testing projects focused on AI data quality, evaluation and software testing.
My portfolio combines:
- AI response evaluation and quality assessment
- Dataset validation and data quality
- Data annotation and structured review
- Manual QA and test case design
- Web testing and browser-based debugging
- API testing and test automation — currently learning
A browser-based tool for validating JSON datasets and identifying common data quality issues.
Demonstrates:
- dataset validation
- missing field detection
- duplicate ID detection
- class distribution analysis
- structured quality reporting
- JavaScript and browser APIs
A lightweight browser-based annotation tool for assigning labels to image data.
Demonstrates:
- data annotation workflow
- structured labeling
- browser-based interaction
- HTML, CSS and JavaScript
I am currently expanding my portfolio toward:
- AI / LLM evaluation
- Data quality and annotation QA
- Manual QA
- Web QA
- API testing
- Playwright automation
The goal is to build portfolio projects around realistic tasks rather than isolated programming exercises.
Testing & QA
- Manual testing
- Test cases
- Bug reports
- Exploratory testing
- Browser DevTools
- API testing
AI & Data
- AI evaluation
- Data annotation
- Dataset quality
- JSON
Technical
- HTML5
- CSS3
- JavaScript
- Git / GitHub
I am interested in remote roles related to AI evaluation, data quality and software testing.
My background in production work taught me to work with structured processes, follow requirements and identify problems in operational workflows. I am now applying the same approach to AI data and software quality.
GitHub: @rawXman