In 2022, artificial intelligence will continue its growth to become the life-changing technology ever developed by human beings. AI’s potential is enormous for businesses in each industry due to the huge amount of data generation. These datasets have to be analyzed at a faster pace, which can be performed swiftly by AI than humans.

AI and machine learning are among the most in-demand skills for today’s workforce. According to a report published WeForum, by 2025, automation will replace 80 million jobs and around 97 million new job roles will be created that divide the labor amongst machines, algorithms, and human beings. As AI is being democratized in new and improved ways, the AI domain will offer great career growth opportunities to the aspirant due to increasing job roles in various industries.

Some of the great career opportunities in the field of AI are Machine learning Engineer, AI Engineer, Data Scientist, Research Scientist, Robotics Engineer, Analytics Manager, and AI Architect.

Machine Learning Engineer

The job of a machine learning engineer involves designing, developing algorithms and programs that enable machines to perform tasks without being directed. He/she should be equipped with data science skills to handle a huge amount of business data. Machine learning engineers have to use data modeling to find data patterns from the high volume of data or predict unforeseen situations.  The job profile of a machine learning engineer differs as the requirements and tasks vary from one organization to other.

AI Engineer

AI Engineer is responsible for developing, programming and training complex algorithms to deploy AI models. Their role is to extract business insights by performing statistical analyses that help to make vital business decisions. To be an AI engineer, the aspirants must have an in-depth understanding of data science, software development, and programming languages. They have to use various tools and techniques for processing data and maintaining AI systems.

Data Scientist

Data scientist gathers relevant data from several sources and evaluates it to draw constructive conclusions. They use their analytical skills to clean and validate data to make sure of the completeness, uniformity, and accuracy of the data. They frequently work with machine learning engineers to develop algorithms that assist in data cleaning for analysis. Once the data is analyzed, a data scientist will solve problems using data-driven solutions. Based on the data patterns and historical information, data scientists will make predictions accordingly.

Robotics Engineer

Robotics Engineers work in the field of automation and robotics. They are responsible for the designing and building of robotic systems and robots that are productive. They are also involved in designing machines that are capable of assembling robots. Since robotic applications differ significantly, robotics engineers have to determine the application requirements and tailor the capabilities of the robots.

Analytics Manager

Analytics managers collect and analyze data to gain valuable business insights that influence decision-making. They coordinate with the team to complete bigger tasks, which may include data collection, analyzing information, and predicting solutions to the business. Analytics managers lead cross-functional projects and work closely with teams across sales, marketing, and products to implement data-driven decisions.

AI Architect

The role of an AI architect is to deliver concrete solutions using the right technologies and has the responsibility to create and maintain architecture with the help of leading AI frameworks. They must have an in-depth understanding of specific architecture, various approaches to implement AI, different AI patterns, capabilities of AI platforms, and data patterns in the organization.

Wrapping Up

AI offers a fascinating learning curve for motivated and interested people who would like to advance in their careers or break into a career in artificial intelligence. The rewarding career opportunities in AI outweigh the time and money invested in learning AI. A master’s degree (M. Tech/M.Sc.) in AI for working professionals from a thought leader in next-gen tech education like REVA Academy for Corporate Excellence-RACE, REVA University will prepare the participants to excel in the artificial intelligence domain.