Artificial Intelligence is the central tenet in the current tech revolution and is the driving force behind new and ongoing developments such as natural language processing as well as speech analysis. It continues to get smarter and is more than likely to keep having an impact on industries and companies in terms of how they operate and what products they can develop. There is a race in terms of investing in the next big AI technology across most sectors to develop products that can do tasks humans can’t do at a lightning-fast pace.  

AI career landscape

It is no wonder, then, that there is a great interest among budding techies for opportunities in the field. Simultaneously, there is a growing need for domain experts and companies in the tech sector who are on the lookout for skilled applicants with a skew towards strategy and creativity. With more and more sophisticated models being developed, companies are looking for AI experts for their respective R&D divisions.

Careers in AI are dynamic, with opportunities prevalent in areas such as machine learning and data science. These advancements in AI are being used to develop products in a wide range of businesses such as banking, health care, security and even astronomy.  

Getting started with AI

To reach an inflection point in a career based on AI, you will need to learn a programming language. Although there are several different programming languages, the most popular one in relation to machine learning and data science is Python. You need to be thorough in the basics and practice a lot before you can venture into machine learning.  

R programming language is another one that you can learn. Although it is used less in machine learning, R programming is used for other aspects of AI, such as tasks related to data science. Machine learning and data science usually blend in real-world applications, so having a good understanding of both languages can be quite helpful.  

Along with programming languages, you would also need to understand different libraries and frameworks that are used in AI. For instance, TensorFlow or PyTorch can help you in writing code at a faster pace. Scikit-learn is another powerful library that has a few statistical modeling tools as well as machine learning kits.

Skills to master

Machine Learning would be one of the main skills you’ll need to master for a career in AI. It essentially involves computer-based algorithms that can learn and improve based on data and through experiences gained via practical applications. Initially, machine learning works with a data sample to make decisions, before taking the help of AI to learn and take intelligent decisions based on data from real-time tasks.  

Along with Machine Learning concepts, it is also important to be skillful in MLOps, a fast emerging domain. It is a core function as it helps streamline the process of taking the machine learning models that have been developed to production and helps in maintaining and monitoring them. With MLOps, you can get faster and higher quality model development. It also helps with scalability as MLOps can help monitor and manage thousands of models and help with continuous integration and deployment.  

Deep Learning is another skill that can be very helpful to progress in a career in AI. It is a branch of machine learning that attempts to mimic the process in which humans gain knowledge. It can help in automating your predictive analysis models and the algorithms tend to be arranged by way of increased complexity and abstraction. It is specifically helpful in collecting large amounts and analysing them with speed and accuracy.  

Big Data is another thriving field of AI. It involves collecting, sorting, and analysing large amounts of data for behavior analysis and other analytical needs. Big Data helps in building state-of-the-art technology products.  

Hiring of AI Engineers peaks

Some of the top companies around the world are looking to hire AI engineers. They are willing to pay top dollar for skilled candidates. Predictably, Amazon is one of the most prolific hirers of AI engineers, considering their expansion through Amazon Web Services. They also collect a lot of customer data through their e-commerce website and need Big Data and Machine Learning to help them offer better and more intuitive products to their customers.  

Accenture is another multinational company looking to hire AI engineers. They provide services related to operations and need analysts in AI for developing innovative products for their clients. Similarly, IBM also hires AI engineers regularly to help its clients with data analysis and collaborating with product developments.  

Tata Consultancy Services, Cognizant Technology Solutions, Infosys and Intel are some of the other top multinational companies constantly looking to hire skilled AI engineers. There are enough and more opportunities in leading tech companies themselves, and if you have the skills and expertise, you can have a promising and rewarding career in AI.