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Artificial Intelligence is transforming industries and sectors by creating higher-value services while contributing to the global economy. Like every business sector, research, education, and healthcare are depending on Artificial Intelligence (AI) for one or the other reason, the jobs in the AI industry is surging and expected to increase by 2.3 million positions by the year 2030.

Many big brands like IBM, Amazon, Microsoft, Accenture; startups, and small businesses as well are using AI. All kinds of industries like transportation, energy, farming, finance, manufacturing, healthcare, cybersecurity, business intelligence, education, construction, and information technology are moving toward this technology.

The World Economic Forum predicts that AI will lead to a net increase of 58 million jobs globally. One-third of the American workforce may have to switch occupations by 2030, suggests McKinsey Global Institute’s recent report. Gartner suggests that Artificial Intelligence will create a business value of USD 3.9 trillion by 2022.

In brief, AI careers are future-proof and will survive well in the future. There are limitless opportunities for professionals to work on AI development and research. Young professionals and students will benefit a lot from this burgeoning field.

Let’s see how to break into an Artificial Intelligence career as an AI Engineer here.

Becoming an AI Engineer

Van Loon says, “AI never stops learning, so you too can’t stop learning. AI has a higher learning curve.”

AI engineering refers to the use of algorithms, computer programming, neural networks, and other technologies for developing AI applications and techniques that possess practical applications in commerce, science, and life activities.

As an AI Engineer, you must extract data from a variety of sources, design algorithms, build and test machine learning models and deploy the models to create AI-powered applications to perform complex tasks. Further, you will be coordinating with data scientists and business analysts to acquire data and solve problems.

Educational requirements:


AI is an emerging field and the Universities differ in giving AI specialization. To start with, a degree in Computer Science, Statistics, Mathematics, Economics, Information Technology, or Finance is preferred. However, holding a master’s degree in Data Science, Computer Science, Cognitive science, or Machine Learning is much appreciated.


There are new undergraduate and graduate programs designed to prepare candidates solely to work with AI in the future. It is helpful to take interdisciplinary courses along with the degrees.

As an AI Engineer, you should have special knowledge in, Linear Algebra, differential and Integral Calculus, Matrices and Linear Transformations, Integration and Approximation, Modern Regression, Probability Theory, Bayesian Networking, and Probabilistic Graphical Models.

Plus, you should get expertise in Computer Systems and Programming; Principles of Imperative Computation and Functional Programming, Data Science Essentials, Parallel and Sequential Data Structures and Algorithms, Logic Programming and Computational Logic, and Agile Software Development.

Further, you should get trained in Machine Learning, Deep Learning, and Reinforcement Learning, Information Theory, Inference, and Learning Algorithms, Neural Networks for Machine Learning, AI Representation, Problem-Solving, Natural Language Processing, Computer Vision and Image Analysis.

To add on, you should be well-versed in Deep reinforcement learning, Applied Machine learning, advanced data analysis, neural computation, autonomous agents, cognitive robotics, strategic reasoning, Robot kinematics, speech processing, human-robot interaction, and computational photography. In addition to technical skills, it is necessary to learn business skills, problem-solving ability, be creative in thinking, and possess industry knowledge.

Mention not to say, there are Artificial Intelligence Certifications provided by recognized institutions and certification bodies that keep you updated with the AI knowledge and skills. It increases your salary by 20-30% as you prove to your employer that you have ready-to-go skills. The best-known Artificial Intelligence Certifications include:

  • Machine Learning Certification Program – eCornell
  • Artificial Intelligence Engineer (AIETM) – Artificial Intelligence Board of America (ARTiBA)
  • Certified Artificial Intelligence Expert TM – Global Tech Council TM

Job opportunities and prospects for AI Engineers

Jobs in AI engineering is promising. Hiring for AI positions has been growing at 74% annually over the past four years. Roles of AI engineers are being created in almost all sectors from technology, automotive industries, sports, to higher education.

As per, the most in-demand AI jobs include Machine learning engineer, Robotics engineer, Computer vision engineer, and data scientist which has grown by 344, 128, 116, and 78 percent respectively in the last four years.

The job prospects are bright for AI engineers. Students and professionals can define their career trajectories in AI by acquiring the necessary skills and knowledge. Learning AI and networking with the right people will help you get jobs in Google, Amazon, Apple, and also companies specializing in niche industries.

Final thoughts

The demand for AI engineers is increasing and is likely to increase further in the coming years owing to advances in computing power, speed, data diversity, and evolution of deep neural networks. The industries using AI are expanding and no industry will be untouched by AI in the future.

Stay in the race! Stay committed and get prepared for the jobs of the future. Learn AI and acquire the most in-demand jobs.