In this digital era that we are living in everyone is obsessed with mobiles, computers and is on the internet, so job portals play an important role in aiding job seekers in their job hunt. It will make them aware of the various job openings, and they will not miss an opportunity. The job is essential for the students who do their graduation, post-graduation, etc. So, we know that there are lots of websites where can we can find the lots of vacancy in various firms but the website is not updated the job vacancy minutely or many of them not updated the job vacancy hourly so we cannot get the minutely updated about the jobs. The vacancy appears quickly on social networking websites like Twitter, LinkedIn, Facebook, etc. as compared to appears on the job websites like indeed.com, monster.com, etc. so many of the people are not on these social media or maybe not regular on the social media, so there is a chance miss the opportunity. Our objective with this paper is to come up with a portal that will provide the user's details about various job openings in respective domains. The portal will stream data from Twitter API to find out the recently published jobs. Classification of relevant and irrelevant tweets is accomplished using the machine-learning algorithm, i.e., Logistic Regression. Using the algorithm, we have measured the 97% accuracy.