Artificial intelligence is growing, and not just in the research labs of the world’s leading universities. Increasingly, businesses are harnessing the power of artificial intelligence and machine learning to optimize their operations and deliver better products to consumers. If you’ve ordered an Uber, browsed Netflix, or added something to your cart on Amazon, you’ve experienced first-hand the impact artificial intelligence can have on our daily lives. In the coming years, this impact will only grow: according to Stanford University’s 2022 AI Index Report, private investment in artificial intelligence in 2021 doubled that of 2020, topping $90 billion worldwide.
To translate this investment of capital into the practical application of AI technologies, companies are increasingly turning to professionals working in the fledgling field of artificial intelligence engineering. Regardless of whether their job title is AI engineer, machine learning engineer, artificial intelligence specialist, or even software engineer, AI engineering professionals focus on ensuring that technical capabilities in the lab can be implemented in the real world.
This pursuit can be lucrative: Glassdoor pegs the median artificial intelligence engineer salary at $119,640 annually. For a machine learning engineer, the median salary climbs to $124,040. Compare these to the average annual salary in the US, which the U.S. Bureau of Labor Statistics estimated to be $58,260 in 2021, or the average annual salary for a web developer, which Indeed pegs at $71,707.
Is artificial intelligence engineering a career path for you?
If helping to implement cutting-edge technology sounds like an exciting career opportunity, you’ve come to the right place. In this article, we’ll elaborate on what exactly artificial intelligence engineering is as well as some common career paths for AI engineers. We’ll also cover what skills are needed to succeed as an AI or machine learning engineer and how you can get started building and honing them in a bootcamp, online bachelor’s degree, or master's program.
What is artificial intelligence engineering?
According to Carnegie Mellon University’s Software Engineering Institute (SEI), AI engineering is “an emergent discipline focused on developing tools, systems, and processes to enable the application of artificial intelligence in real-world contexts.” This goal of reconciling the virtual with the real means that AI engineering involves multiple disciplines, including, according to SEI, systems engineering, computer science, and human-centered design.
Since AI engineering is so new, different people will offer different accounts of what the guiding principles should be. That said, the SEI’s three pillars of AI engineering are instructive as to some of the problems an artificial intelligence engineer encounters every day: