Machine Learning Engineer Salary: How Much Can You Make?

Machine learning (ML) engineers research, design, and develop critical artificial intelligence on data science teams. Whether they’re working on algorithms to power your Spotify recommendations or creating algorithms to make real-time stock predictions, machine learning engineers are in high demand in many industries. As a result, they're well-compensated for their in-depth knowledge and ability to make decisions that drive profits.

In this article, we'll discuss what machine learning engineers do and the average salaries by experience and location. Afterward, if you're interested in pursuing a career in machine learning, consider enrolling in DeepLearning.AI's Machine Learning Specialization. You'll learn AI concepts and develop practical machine learning skills in this beginner-friendly program.

What is an average machine learning engineer salary? 

The average salary of a machine learning engineer is impacted by many factors, including experience, industry, and geographic location. However, according to various salary aggregate sites, the average US salary for a machine learning engineer ranges from $116,416 to $140,180, which is significantly more than the median salary in the US [1]. 

Machine learning engineer salaries by experience

Experience has a big impact on what machine learning engineers can expect to make. Generally, the more experience a machine learning engineer has, the more they can expect to make in their role. According to Glassdoor, the experience breaks down as follows [2]:

• 0-1 years: $127,350 

• 1-3 years: $144,572

• 4-6 years: $150,193

• 7-9 years: $154,779

• 10-14 years: $162,356

• 15+ years: $170,603

Those in more senior positions can typically expect to make even more. For example, according to Glassdoor, the average annual salary that a senior machine learning engineer makes is $140,180 across all years of experience [2].

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Machine learning engineer industries 

As data becomes increasingly more valuable, so too do machine learning engineers capable of manipulating it with artificial intelligence. As a result, there are many industries where machine learning engineers can expect to find work. Here are the top five sectors, according to AI magazine [3]: 

• Health care

• Transportation

• Finance 

• Agriculture 

• Cybersecurity

Salaries for related jobs in machine learning

Machine learning engineer isn’t the only game in town for those with the required skill set. According to Glassdoor, here’s how other similar jobs’ salaries stack up: 

Software engineer - machine learning: $155,960

Research engineer: $122,747

Machine learning research scientist: $160,007

Machine learning scientist: $158,229

Machine learning engineer salaries by location 

Typically, salaries vary from region to region. Every location has its own cost of living and market competition, which inevitably impacts the salary that a machine learning engineer can expect to make. 

Here are the average salaries for machine learning engineers across the country – from the west coast to the east, the midwest to the south – courtesy of Glassdoor: 

Job outlook for machine learning engineers 

The job outlook for machine learning engineers is positive. According to the Bureau of Labor Statistics, computer and information research scientists – the group under which machine learning engineers typically fall – are projected to grow by 23 percent between 2022 and 2032 [4]. 

In 2019, meanwhile, Indeed ranked machine learning engineer as the number one job in the United States, noting its high salary and the 344 percent job growth seen between 2015 and 2018 as key reasons [5]. 

Learn about machine learning with Coursera

Becoming a machine learning engineer takes time and dedication. To get started, consider taking Stanford and DeepLearning.AI's Machine Learning Specialization. Over three courses, you'll learn foundational machine learning concepts and gain practical skills development, including building and training a neural network with TensorFlow to perform multi-class classification.

Looking to advance your machine learning skills? Johns Hopkins' Applied Machine Learning Specialization is a three-course program designed for intermediate learners with an understanding of programming fundamentals and familiarity with introductory statistics and linear algebra. You'll learn machine learning techniques to solve real-world problems in data processing, computer vision, and neural networks.