Artificial intelligence experts continue to be in high demand

To reach an inflection point in an AI-based career, you will need to learn a programming language; although there are several different programming languages, the most popular in machine learning and data science is Python

Artificial intelligence is the central tenet of the current technological revolution and is driving new and ongoing developments such as natural language processing as well as speech analytics. It continues to get smarter and is more than likely to continue to impact industries and businesses 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 in most industries to develop products that can perform tasks that humans cannot at a blistering pace.

AI career landscape

It’s no wonder, then, that there is great interest among aspiring techies for opportunities in the field. At the same time, there is a growing need for domain experts and technology companies who are looking for qualified candidates with a penchant for strategy and creativity. With increasingly sophisticated models being developed, companies are looking for AI experts for their respective R&D divisions.

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

Get started with AI

To reach an inflection point in an AI-based career, you will need to learn a programming language. Although there are several different programming languages, the most popular when it comes to machine learning and data science is Python. You need to master the basics and practice a lot before jumping into machine learning.

R programming language is another you can learn. Although less used in machine learning, R programming is used for other aspects of AI, such as data science tasks. Machine learning and data science usually blend into real-world applications, so having a good understanding of both languages ​​can be very useful.

Along with programming languages, you also need to understand the different libraries and frameworks used in AI. For example, TensorFlow or PyTorch can help you write code faster. Scikit-learn is another powerful library that contains some statistical modeling tools as well as machine learning kits.

Skills to master

Machine learning would be one of the main skills you need to master for a career in AI. They are basically computer algorithms that can learn and improve based on on data and through experiences acquired through practical applications. Initially, machine learning works with sample data to make decisions, before taking the help of AI to learn and make intelligent decisions based on data from real-time tasks.

Besides machine learning concepts, it is also important to be skilled in MLOps, a rapidly emerging field. This is a critical feature as it helps streamline the process of bringing the machine learning models that have been developed into production and helps to maintain and monitor them. With MLOps, you can achieve faster and better model development. It also helps with scalability, as MLOps can help monitor and manage thousands of models and facilitate continuous integration and deployment.

Deep learning is another skill that can be very useful for advancing in an AI career. It is a branch of machine learning that attempts to mimic the process by which humans acquire knowledge. It can help automate your predictive analytics models, and algorithms tend to be organized in ways that increase complexity and abstraction. It is particularly useful for collecting large quantities and analyzing them quickly and accurately.

Big Data is another flourishing area of ​​AI. It involves collecting, sorting, and analyzing large amounts of data for behavior analysis and other analytical needs. Big Data helps create cutting-edge technological products.

Hiring peaks for AI engineers

Some of the biggest companies in the world are looking to hire artificial intelligence engineers. They are willing to pay top dollar for qualified candidates. Predictably, Amazon is one of the most prolific recruiters of AI engineers, given 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 deliver better and more intuitive products to their customers.

Accenture is another multinational looking to hire artificial intelligence engineers. They provide operations-related services and need AI analysts to develop innovative products for their clients. Similarly, IBM regularly hires artificial intelligence engineers to help customers analyze data and collaborate on product developments.

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

Sam D. Gomez