Start Your Machine Learning Engineer Career

Machine learning skills can open the door to a wide range of careers, as more and more companies seek to harness these techniques and artificial intelligence (AI) to automate a growing range of processes. Some companies may specifically hire for machine learning engineers, but machine learning skills can also be important for data scientists, data analysts, and data engineers.

There are more specialized roles available for machine learning experts, too. Many companies in the financial industry may employ business intelligence analysts and decision scientists who can leverage machine learning skills to automate systems for delivering market insights. And companies building Internet of Things (IoT) that rely on voice recognition or other human inputs may employ natural language processing engineers or human-centered machine learning designers.‎

Machine learning is in some ways a hybrid field, existing at the intersection of computer science, data science, and algorithms and mathematical theory. On the computer science side, machine learning engineers and other professionals in this field typically need strong software engineering skills, from fundamentals like confident programming and coding ability to big picture familiarity with system design principles.

A familiarity with data science concepts is also important, particularly skills in data modeling and evaluation to ensure that the algorithms perform well and become more accurate over time. And, because machine learning relies heavily on algorithms as well as the statistics and probability principles that underlie them, a solid theoretical background in mathematics can also be valuable.‎

The average base pay for a machine learning engineer in the US is $127,712 as of March 2024 [1].

According to a December 2020 study by Burning Glass, demand for AI and machine learning skills is projected to grow by 71 percent 2020-2025. The same study reports a $14,175 salary premium associated with these skills [2].‎