Salaries in AI | Towards AI
Artificial Intelligence: Salaries Heading Skyward
While the average salary for a Software Engineer is around $100,000 to $150,000, to make the big bucks you want to be an AI or Machine Learning (Specialist/Scientist/Engineer.)
August 29, 2018, by Stacy Stanford — Last updated: September 20, 2019
Artificial intelligence salaries benefit from the perfect recipe for a sweet paycheck: a hot field and high demand for scarce talent. It’s the ever-reliable law of supply and demand, and right now, anything artificial intelligence-related is in very high demand.
According to Indeed.com, the average IT salary — the keyword is “artificial intelligence engineer” — in the San Francisco area ranges from approximately $134,135 per year for “software engineer” to $169,930 per year for “machine learning engineer.”
However, it can go much higher if you have the credentials firms need. One tenured professor was offered triple his $180,000 salary to join Google, which he declined for a different teaching position.
However, the record, so far, was set in April when the Japanese firm Start Today, which operates the fashion-shopping site Zozotown, posted new job offerings for seven “genius” AI tech experts, offering annual salaries of as much as 100 million yen, or just under USD $1 million.
Key Sectors for AI Salaries
Scoring a top AI salary means working in the “right” sector. While plentiful, AI jobs are mainly in just a few sectors — namely tech — and confined to just a few big and expensive cities. Glassdoor, another popular job search site, notes that 67% of all AI jobs listed on its site are located in the Bay Area, Seattle, Los Angeles, and New York City.
It also listed Facebook, NVIDIA, Adobe, Microsoft, Uber, and Accenture as the five best AI companies to work for in 2018, with almost 19% of open AI positions. The average annual base pay for an AI job listed on Glassdoor is $111,118 per year.
Glassdoor also found financial services, consulting and government agencies are actively hiring AI engineering and data science professionals. This includes top firms like Capital One, Fidelity, Goldman Sachs, Booz Allen Hamilton, EY, and McKinsey & Company, NASA’s Jet Propulsion Laboratory, the U.S. Army, and the Federal Reserve Bank.
However, expect the number of jobs and fields to expand considerably in the near future. A recent report from Gartner said that AI will kill off 1.8 million jobs, mostly menial labor, but the field will create 2.3 million new jobs by 2020, such statement is emphasized by a recent Capgemini report that found that 83% of companies using AI say they are adding jobs because of AI.
Best Jobs for AI Salaries
The term “AI” is rather broad and covers a number of disciplines and tasks, including natural language generation and comprehension, speech recognition, chatbots, machine learning, decision management, deep learning, biometrics, and text analysis and processing. Given the level of specialization each requires, not many professionals can master more than one discipline.
In short, finding the best AI salary calls for actively nurturing the right career path.
While the average pay for an AI programmer is around $100,000 to $150,000, depending on the region of the country, all of these are in the developer/coder realm. To make the big money you want to be an AI engineer. According to Paysa, yet another job search site, an artificial intelligence engineer earns an average of $171,715, ranging from $124,542 at the 25th percentile to $201,853 at the 75th percentile, with top earners earning more than $257,530.
Why so high? Because many come from non-programming backgrounds. The IEEE notes that people with PhDs in sciences like biology and physics are returning to school to learn AI and apply it to their field. They need to straddle the technical, knowing a multitude of languages and hardware architectures, with an understanding of the data involved. The latter makes engineers rare and thus expensive.
Why Are AI Salaries So High?
The fact is, AI is not a discipline you can teach yourself as many developers do. A survey by Stack Overflow found 86.7% of developers were, in fact, self-taught. However, that is for languages like Java, Python, and PHP, not the esoteric art of artificial intelligence.
It requires advanced degrees in computer science, often a Ph.D. In a report, Paysa found that 35 percent of AI positions require a Ph.D. and 26 percent require a master’s degree. Why? Because AI is a rapidly growing field and when you study at the Ph.D. level and participate in academic projects, they tend to be innovative if not bleeding edge, and that gives the student the experience they need for the work environment.
Moreover, it requires multiple disciplines, including Python, C++, STL, Perl, Perforce and APIs like OpenGL and PhysX. In addition, because the AI is doing important calculations, a background in physics or some kind of life science is necessary.
Therefore, to be an effective and in-demand AI developer you need a lot of skills, not just one or two. Indeed lists the top 10 skills you need to know for AI:
1) Machine learning
4) Data science
6) Big Data
8) Data mining
As you can see, that is a wide range of skills and none of them is learned overnight. According to The New York Times, there are fewer than 10,000 qualified AI specialists in the world. Element AI, a Montreal company that consults on machine learning systems, published a report earlier this year that there were 22,000 Ph.D.-level computer scientists in the world who are capable of building AI systems. Either way, that is too few for the demand reported by Machine Learning News.
Competing Employers Drive Salaries Higher
With so few AI specialists available, tech companies are raiding academia. At the University of Washington, six of 20 artificial intelligence professors are now on leave or partial leave and working for outside companies. In the process, they are limiting the number of professors who can teach the technology, causing a vicious cycle.
US News and World Report lists the top 20 schools for AI education. The top five are:
1) Carnegie Mellon University, Pittsburgh, PA
2) Massachusetts Institute of Technology, Cambridge, MA
3) Stanford University, Stanford, CA
4) University of California — Berkeley, Berkeley, CA
5) University of Washington, Seattle, WA
With academia being raided for talent, alternatives are popping up. Google, which is hiring any AI developer it can get its hands on, offers a course on deep learning and machine-learning tools via its Google Cloud Platform Website, and Facebook, also deep in AI, hosts a series of videos on the fundamentals of AI such as algorithms. If you want to take courses online, there is Coursera and Udacity.
Basic computer technology and math backgrounds are the backbones of most artificial intelligence programs. Linear algebra is as necessary as a programming language since machine learning performs analysis on data within matrices, and linear algebra is all about operations on matrices. According to Computer Science Degree Hub, coursework for AI involves the study of advanced math, Bayesian networking or graphical modeling, including neural nets, physics, engineering and robotics, computer science and cognitive science theory.
Some things cannot be taught. Working with artificial intelligence does not mean you get to offload the work on the computer. It requires analytical thought process, foresight about technological innovations, technical skills to design, the skill to maintain and repair technology and software programs as well as algorithms. Therefore, it is easy to see why skilled people are so rare — which will drive AI salaries only higher.