What’s the best job in the United States? According to a new study by Indeed, it’s machine learning engineer. The job-posting website reached that conclusion after analyzing two factors: fastest job-posting growth between 2015 and 2018, and highest average salaries. In other words, people are hiring lots of machine learning engineers, and they’re willing to pay top dollar for them (be prepared for your interview by knowing the top machine learning engineer interview questions and answers)—Indeed pegged the average machine learning engineer salary at $146,085, and its growth between 2015 and 2018 at 344 percent. That outpaced other technology jobs on the list, including full-stack developer (which came in third with a $114,316 average salary and 206 percent growth) and Salesforce developer ($112,031 average salary and 129 percent growth, good for tenth place). In big tech hubs such as New York and San Francisco, the salaries for tech pros skilled in machine learning and artificial intelligence (A.I.) only increase. According to an analysis that Dice ran late last year, machine learning experts could pull down an average of $165,760 in New York City, and $154,096 in San Francisco—and that’s before you throw in perks and benefits such as flexible hours, stock options, and healthcare. If you want to become a machine learning engineer (or any kind of expert in the field), it’s going to take quite a bit of education. Fortunately, there are a variety of online materials to help with that, much of it produced by companies (which means those materials are often slanted to cover a particular platform or tool). For instance, Amazon’s machine-learning offering includes 30 self-paced courses. These videos, labs, and text-based lessons dig into machine learning’s fundamentals and how those apply to real-world scenarios, which makes sense because these are the materials supposedly used to train Amazon’s in-house developers and engineers. For those looking for something a bit more advanced, Bloomberg offers a free online course in machine learning, designed for developers who already have some experience with the technology. Then there’s Google’s (also free) course with 25 lessons and more than 40 exercises; it takes around 15 hours to complete, and includes lots of video of Google engineers describing the nuances of A.I. and machine learning. That’s in addition to the machine-learning courses offered by schools, as well as online-learning platforms. In short, there are lots of resources out there—provided you’re willing to make the commitment. But as the data shows, the time and resources devoted to integrating machine learning into your skillset can really pay off, salary-wise, if you pursue a career as a machine learning engineer.