Over the past couple of years, the Covid-19 pandemic followed by the intrusion of its variants has has a devastating impact on the global economy. Employment across many industries was under great threat. However, one thing that the catastrophe left unscathed was artificial intelligence. Artificial intelligence came into existence when humans thought of making machines that imitate human behavior. The core aspect of creating AI was to make technology recreate human insights in a better and advanced way.

Artificial intelligence had an eventful decade so far. With 2021 bringing more into play, technology has stronghold its place in every ecosystem. Especially, business organizations are enhancing their AI capabilities to streamline routine processes. Starting from attending to customer queries to powering autonomous vehicles, the influence of artificial intelligence is no joke. Besides, critical fields like healthcare, education, and space are adopting AI to sophisticate their existing features and bring in innovation.

Artificial intelligence is considered the future technology. It is already making a significant impact on modern enterprises. AI has sparked several innovations and brought digital disruption to diverse industries. It has also changed the jobs market forever. As more and more companies leverage this technology, AI has become the most in-demand skills to land a job in an organization, regardless of industry.

The ideal candidate will be responsible for using NLP and ML techniques to bring order to unstructured data. He/she should have experience in the latest techniques in AI, NLP, machine learning, including Deep Learning approaches. The aspirant will work within the engineering team to design, code, train, test, deploy and iterate on enterprise-scale machine learning systems.

We are a data science corporate training firm looking to deepen our bench of data science and data engineering instructors that can teach virtual, synchronous and asynchronous courses on topics such as machine learning, statistical modeling, programming in Python and R, data analysis, data visualization, data engineering, and building data products.