Software Engineer working on a project to develop skills

Machine learning engineers play an increasingly crucial role in many companies’ strategies. The algorithms created by machine learning engineers continually optimize themselves, which is useful in a variety of contexts, from improving speech recognition to learning customer preferences.

As you might expect, it takes a considerable amount of time and resources to master the fundamentals of machine learning, and tech pros who accomplish this can earn significant salaries, along with other benefits such as stock options. But how high can compensation go? In some of the nation’s largest tech hubs, the payouts can reach well into six figures once you factor in bonus, base salary, and equity.

Blind, which anonymously surveys tech pros about various issues, recently crunched its data to determine the 24 highest-paying cities for machine learning engineers. Here’s a breakdown of the top ten:

“The average salary of a machine learning engineer in the United States is between $112,185 and $216,800 in 2023,” Blind stated in a note accompanying the data. “Salaries can be significantly higher for senior machine learning engineers or directors of machine learning engineering.”

If you’re interested in machine learning as a career, keep in mind that you’ll face a barrage of technical questions during an interview for a machine learning engineer position. “Soft skills” such as communication and empathy are just as valuable; make sure you come to any interview prepared with stories about how you’ve used those skills to secure stakeholder buy-in and help guide teams. On the technical side, top skills include:

Just dipping your toe into machine learning? Fortunately, there are tons of online resources to give you a sense of it, including w3schools, Amazon (with a heavy AWS focus), and Google coursework (focusing on the TensorFlow APIs). Once you’ve mastered the basics, you can consider self-learning or taking a formal course.