Project
PublicLink
Contributed AI-powered features to PublicLink, enabling structured extraction from CVs and job posts and improving matchmaking for candidates and vacancies.
Bubble.ioAI parsingMatching engine
- Tool
- Bubble.io
- Visit here
- Open live site
Key contributions
- Engineered a CV parsing pipeline extracting structured candidate data
- Designed a job description parser to extract key fields from postings
- Built a bidirectional AI matching engine for candidates and vacancies
- Ranked top matches by skill and experience alignment
The core focus was turning free-form documents into queryable structured data and then using that structure to rank matches on both sides of the marketplace. This reduced manual input, improved search quality, and helped users quickly find relevant opportunities and candidates.
Outcomes and highlights
- Structured parsing outputs: skills, experience, education, role history.
- Queryable job fields: seniority, responsibilities, location, required skills.
- Top 5 best matches surfaced for both job seekers and vacancies.
Technologies Used
Bubble.ioAI-assisted parsingData structuringMatching and ranking logic
- Bubble.io
- AI-assisted parsing
- Data structuring
- Matching and ranking logic
My Role
Built CV and job post parsing pipelines and implemented a bidirectional matching engine surfacing top-ranked candidates and opportunities.
Gallery
Screens and flows
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Visit the live website: PublicLink