How Much Do AI Engineers Make? 2024 Salary Guide

By 2030, artificial intelligence (AI) could contribute up to $15.7 trillion to the global economy, which is more than China and India’s combined output today, according to PricewaterhouseCoopers’ Global Artificial Intelligence Study [1]. Organizations are turning to AI to help drive efficiency and profits.

AI engineers help rethink how we use machine learning (ML) algorithms, models, and tools to power our products, services, and global systems. They can easily make a six-figure salary because this type of work requires plenty of technical expertise that is in high demand.

In this article, you’ll learn how much an AI engineer earns. We’ll break it down by experience, industry, and location, with tips for boosting your salary.

What is an average AI engineer’s salary?

AI engineers can earn an annual median salary of $136,620, according to the US Bureau of Labor Statistics [2]. According to Glassdoor, the median base salary for an AI engineer is $108,043 in the United States [3]. 

While the salary range for AI engineers varies, these salary figures are significantly higher than the mean annual salary across all occupations in the United States, $58,260 [4].

Read more: What Is an AI Engineer? (And How to Become One)

Job outlook for AI engineers

For AI engineers, there is a projected job growth of 23 percent between 2022 and 2032, which is much faster than the average for all occupations (5 percent) [2].

AI engineers typically work for companies helping them improve their products, software, operations, and delivery. They tend to be employed in the technology, finance, healthcare, and consulting industries.

Hiring growth for artificial intelligence specialists, including engineers, has grown 74 percent annually for the past four years, according to LinkedIn’s 2020 Emerging Jobs Report [5].

Several factors can influence how much you earn as an AI engineer. Let’s take a closer look at how experience, industry, and location can impact your earning potential.

AI engineer salaries by experience

One of the biggest factors that can influence your salary is your level of experience. It makes sense—the more experience you have working as an AI engineer, the more expertise you have, and the more you can expect to earn.

Here’s how experience can impact your AI engineer salary, according to Glassdoor [6]:

• 2 to 4 years (AI Engineer or Senior AI Engineer): $106,894

• 5 to 7 years (Lead AI Engineer): $128,396

• 8+ years (Principal Machine Learning Engineer): $145,503

• 8+ years (Vice President of Machine Learning): $172,715

Moving into leadership roles such as director or vice president of ML or AI can boost your salary by tens of thousands of dollars. However, you might choose to focus on your expertise rather than managing a team, in which case you can earn more by switching companies or negotiating a higher salary by proving your value.

AI engineer salaries by industry

Not every industry requires AI engineers, but for those that do, such as tech, finance, health care, and retail, AI engineer salaries can vary widely. Typically, salary ranges reflect the respective industries. For example, technology and finance companies tend to pay well across the board, so AI engineers who work for these industries will likely have salaries that are higher than average.

AI engineer salaries by location

Where you live can also impact how much you earn as an AI engineer. In general, working for companies based in big cities like New York, San Francisco, Washington, DC, Boston, and Chicago correlates to a higher salary. This is in part due to the higher cost of living in those areas. 

As companies continue to employ a geographically dispersed workforce that includes remote workers, employers may choose to offer location-based salaries. However, this can become tricky as these salaries must also account for merit and experience level, so location-based salaries can be considered unfair.

According to Glassdoor, these are the annual base salaries for AI engineers in the following large US cities [6]:

• San Francisco, CA: $136,287

• Chicago, IL: $102,934

• New York, NY: $123,403

• Los Angeles, CA: $113,298

• Boston, MA: $106,176

• Houston, TX: $105,172

• Washington, DC: $105,338

Tips for earning more

Say you’re an AI engineer who’s been working for a few years. Here are a few ways you can boost your earning potential:

• Get a master’s degree: While it’s not necessary at all to have a master’s degree to land an AI engineer role (or work your way up to one), approximately 17 percent of AI engineers or specialists have their master’s [7]. That’s compared to 63 percent who have a bachelor’s degree [7]. A master’s degree can help you negotiate a higher salary because you’ll have a solid credential and expertise to back up your work experience.

• Increase your technical skills: In the field of AI and machine learning, there is always more to learn. Keeping up with technical skills, especially updated tools and systems, as well as expanding your repertoire of algorithm and modeling techniques, can help you earn more. Drilling down into a particular industry can also boost your salary.

• Negotiating: One of the most common mistakes job seekers make is not negotiating, or not negotiating their full earning potential. According to Forbes, 70 percent of managers expect negotiation when they make a job offer but don’t state that the offer is flexible [8]. If you choose not to negotiate, that wage gap can increase over time and keep you from reaching your full earning potential.

Salaries for jobs related to AI engineer

Curious what jobs are similar to AI engineers, and what they earn? Take a look at the salary breakdown [6]:

• Machine learning engineer: $106,894

• Software engineer: $100,879

• Software developer: $94,900

• Data engineer: $96,277

• Data scientist: $106,261

Start learning today

Get started in a high-earning career as an AI engineer. Enroll in IBM’s AI Engineering professional certificate to learn how to provide business insights from big data using machine learning and deep learning techniques.