Advanced Online Job Portal

Suma Soft Developed Ruby on Rails Based Advanced Online Job Portal Using AI & ML to Streamline Recruitment Process

Client’s Background

Our client is one of the leading employment service providers. They are on the move to provide advanced job portals for job seekers, employers, and vendors to cater to the best jobs and program recommendations using advanced AI and ML-based algorithms.

Project Requirements

The emerging economy demands the situation to change. The recruitment should be time-saving, cost-effective and at the same time should search out the qualified candidates. Through the desired web application, the client is looking to connect companies and job seekers. Job seekers looking for a pair of technologies can quickly find and train themselves for their new target profession. The platform is meant to provide job seekers with accurate information and guidance on technical skills or other competencies required for the position.

Portal recommends courses, books, and other material to help candidates develop advanced skills quickly and achieve their desired profession. In addition, the application helps the job seeker to articulate and visualize their accumulated technological know-how.

On the other hand, employers can find a well-defined technology expert they need using the web application. This platform is meant to help employers find the best-suited talents filtered by AI & ML-based algorithms.

Solution

Suma Soft’s experienced web development team thoroughly researched and brainstormed the idea before starting the development process. At the end of the discovery phase, the “Who, Why, What, When, and Where” of the project were thoroughly scrutinized.

The portal was built using Ruby on Rails to integrate multiple languages through its fantastic Internationalization library.
‘Distance’ based algorithms were implemented to find the best-calculated results without depending on third-party scientific libraries.
A fully featured dashboard was designed to help Employers see what they want as soon as they log in.
An Application Minimalistic Typing approach was provided where users can get the result they want with less to minimal interaction with the keyboard.
Multiuser monolith application was developed to handle the load and deployed on a cloud platform with 99.99% availability.
AI & ML-based recommendation engine was implemented to bridge the gap between job seeker and employer.