Project Overview

The customer needed to develop an AI-based CV platform that would help him match candidates with companies based on NLP models, which would automatically analyze the candidate's resume, extract contact details and skills.
To this end, our team used:
-  name, address, and addresses extractors based on Stanford core NLP, NLTK tools;
-  skills parser based on a custom skill-set model, that produced normalized-form skills and word2vec vectors to match resumes on the proximity of skills, and match proposals from companies with candidate CVs based on skills;
-  high-load service to manage relearning and work of ML model, including parallelism, caching, Graylog server to monitor performance.
By automating the analysis of candidates' resumes, the AI-powered CV Jobs Platform streamlined the recruitment workflow, saving valuable time and resources. The advanced skill matching and company proposal features ensured that candidates optimally corresponded with companies, leading to better job placements.
With our solution, the client gained a competitive edge in the job market, successfully connecting candidates and companies in a meaningful and impactful way.
Python 3, Flask, Celery, DynamoDB, Redis, Tensorflow, Keras, NLTK, log4j, graylog, swagger, AWS Lambda, AWS triggers.


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