Web Based CV parser, AI matching and search engine
Budget: $10 – $350 USD
Our specification for this job:
Looking for an ML Engineer/Full stack developer with already developed web ready CV/resume parser that includes job parser, job matching, search engine, Boolean search.
Parser:
A CV/resume parser helps us automatically store, organize, and analyze resume data to find the best candidate. It is a component that automatically segregates the information into various fields and parameters like contact information, educational qualification, work experience, skills, achievements, professional certifications to quickly help us identify the most relevant resumes based on our criteria.
It should parse resumes of all formats including PDF, doc, docx, HTML, RTF
It should be easy to integrate with our existing website.
Customizable category weights for the ranked resumes (ability to change weighting on things like experience, skills, management, industry, education, etc)
Real-time ranking updates as weights are changed on web UI
Skills auto-complete on web UI search from integrated search engine
It should contain a detailed library of taxonomies to identify candidate skills.
It should parse multilingual resumes/CVs that automatically identifies region and language to parse information.
It should extract the complete resume information in maximum data fields.
Uses deep learning algorithm for improved extraction and smarter identification of resume data for better search results.
Include bulk import that allows a resume/job parser to parse multiple resumes/jobs in a go.
Search & Match Engine:
Search & Match Engine automatically provides similar matches for Resume/CV and JD/Vacancy in the following ways:
Resume/CV to JDs/Vacancies
JD/Vacancy to Resumes/CVs
Resume/CV to Resumes/CVs
JD/Vacancy to JDs/Vacancies
Looking for an ML Engineer/Full stack developer with already developed web ready CV/resume parser that includes job parser, job matching, search engine, Boolean search.
Parser:
A CV/resume parser helps us automatically store, organize, and analyze resume data to find the best candidate. It is a component that automatically segregates the information into various fields and parameters like contact information, educational qualification, work experience, skills, achievements, professional certifications to quickly help us identify the most relevant resumes based on our criteria.
It should parse resumes of all formats including PDF, doc, docx, HTML, RTF
It should be easy to integrate with our existing website.
Customizable category weights for the ranked resumes (ability to change weighting on things like experience, skills, management, industry, education, etc)
Real-time ranking updates as weights are changed on web UI
Skills auto-complete on web UI search from integrated search engine
It should contain a detailed library of taxonomies to identify candidate skills.
It should parse multilingual resumes/CVs that automatically identifies region and language to parse information.
It should extract the complete resume information in maximum data fields.
Uses deep learning algorithm for improved extraction and smarter identification of resume data for better search results.
Include bulk import that allows a resume/job parser to parse multiple resumes/jobs in a go.
Search & Match Engine:
Search & Match Engine automatically provides similar matches for Resume/CV and JD/Vacancy in the following ways:
Resume/CV to JDs/Vacancies
JD/Vacancy to Resumes/CVs
Resume/CV to Resumes/CVs
JD/Vacancy to JDs/Vacancies