Artificial intelligence (AI) careers are at the heart of emerging IT innovations such as robotisation, the Internet Chabot, DevOps stages and quantum technology, causing a stir in major IT businesses including Google, IBM, Facebook, and LinkedIn. It’s not just about following the trend but looking at facts hold the key. The demand and supply gap for AI professionals in 2021 stood at a whopping 50 per cent as per the ‘India’s Tech Industry Talent: Demand-Supply Analysis’ report from NASSCOM.

 Source: NASSCOM 

With 82% of Indians considering changing jobs in 2022, sensing the importance and demand we have listed down the top 5 career options (in alphabetical order) in AI for you. 

1| AIOps Engineer 

AIOps refers to the strategic application of artificial intelligence, machine learning, and machine reasoning technologies across IT operations in order to simplify and streamline processes while also maximising the utilisation of IT resources. A good chunk of human resources is dedicated to real-time performance monitoring and anomaly identification in medium and large businesses. Candidates for this position should have knowledge in the field of cloud technologies, networking, and security. 

2| Big Data Engineer 

The velocity and volume of data are hitting an all-time high with the total volume of global data is expected to reach 175 ZB by 2025. But it's useless until it's processed and analysed properly. Big data is processed in order to extract useful information, which enhances overall performance. Big Data Engineers are professionals who are responsible for developing, maintaining, testing and evaluating a company’s big data infrastructure. To start with a Big Data Engineer should be familiar with any popular programming language, such as C++, Java, or Python. Following programming, in-depth knowledge of DBMS and SQL is required. 

3| Data Scientist 

Data scientists deal with the data and interpret it, whereas data engineers focus on establishing and managing data infrastructures. Computer scientists, statisticians, and mathematicians are among the most common technical backgrounds for data scientists. Although most data scientists have a master's degree in the field, it is not compulsory though. Knowledge of databases, statistics, probability, mathematical analysis, and mastering of at least one programming tool such as R, Python and SAS are the basics to focus on. 

4| IoT Specialist 

An IoT architect is in charge of developing strategies and monitoring the implementation of all IoT solutions within a company. Along with extensive experience, the position necessitates programming, hardware design, and architecture expertise. A specialist needs to propose and plan the creation of digital solutions based on emerging smart technologies, taking into account costs, resources, and time constraints. Also, the task involves collaboration with programming and data analysis experts to design and develop complex technology solutions. 

5| Machine Learning Engineer 

A machine learning engineer is an IT professional who researches, develops, and constructs self-running artificial intelligence systems with the purpose of automating predictive models. Machine learning engineers design and develop AI algorithms that can learn and make predictions. A basic understanding of the fundamentals of Python programming, programming skills in R, C++, and Octave, an understanding of data modelling and a good understanding of statistics and probability holds the key. 

Summing up, to pursue AI as a career, one must have a good understanding of mathematics and basic programming skills. One must be enthralled by statistics and the handling of data. Obtaining a CS degree is the icing on the cake.