Artificial intelligence engineers use their technical expertise to program machines to think like the human brain. Here’s how much they’re earning—by experience, industry, and location.
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 . Organizations are turning to AI to help power their business decisions, increase efficiency, and ultimately, become more profitable.
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.
Falling under the category of Computer and Information Research Scientist, AI engineers can earn an annual median salary of $131,490, according to the US Bureau of Labor Statistics . According to Glassdoor, the median base salary for an AI engineer is $104,410 in the United States .
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 .
For AI engineers, there is a projected job growth of 21 percent between 2021 and 2031, which is much faster than the average for all occupations (5 percent) .
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 .
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.
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 :
2 to 4 years (AI Engineer or Senior AI Engineer): $137,368
5 to 7 years (Lead AI Engineer): $139,246
8+ years (Principal Machine Learning Engineer): $148,879
8+ years (Director of Machine Learning): $153,183
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.
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.
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 :
San Francisco, CA:$118,542
Chicago, IL: $121,002
New York, NY:$108,332
Los Angeles, CA: $106,815
Boston, MA: $101,995
Washington, DC: $96,537
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 . That’s compared to 63 percent who have a bachelor’s degree . 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 . If you choose not to negotiate, that wage gap can increase over time and keep you from reaching your full earning potential.
Curious what jobs are similar to AI engineers, and what they earn? Take a look at the salary breakdown :
Machine learning engineer: $100,805
Software engineer: $96,466
Software developer: $85,019
Data engineer: $98,307
Data scientist: $100,167
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.
Launch your career as an AI engineer. Learn how to provide business insights from big data using machine learning and deep learning techniques.
20,715 already enrolled
Average time: 9 month(s)
Learn at your own pace
Skills you'll build:
SciPy and scikit-learn, Machine Learning, regression, classification, Hierarchical Clustering, Deep Learning, Artificial Neural Network, Artificial Intelligence (AI), keras, Opencv, Image Processing, Computer Vision
PricewaterhouseCoopers. “Sizing the prize: What’s the real value of AI for your business and how can you capitalise?, https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf.” Accessed August 30, 2022.
US Bureau of Labor Statistics. “Computer and Information Research Scientists, https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm.” Accessed August 30, 2022.
Glassdoor. “AI Engineer Salaries, https://www.glassdoor.com/Salaries/ai-engineer-salary-SRCH_KO0,11.htm.” Accessed August 30, 2022.
US Bureau of Labor Statistics. “Occupational Employment and Wage Statistics, https://www.bls.gov/oes/current/oes_nat.htm#00-0000.” Accessed August 30, 2022.
LinkedIn. “2020 Emerging Jobs Report, https://business.linkedin.com/content/dam/me/business/en-us/talent-solutions/emerging-jobs-report/Emerging_Jobs_Report_U.S._FINAL.pdf.” Accessed August 30, 2022.
Glassdoor. “AI Engineer Career Path, https://www.glassdoor.com/Career/how-to-become-ai-engineer_KO14,25.htm.” Accessed August 30, 2022.
Zippia. “Artificial Intelligence Specialist Requirements, https://www.zippia.com/artificial-intelligence-specialist-jobs/education/.” Accessed August 30, 2022.
Forbes. “The Most Critical Reason You Need To Negotiate & How To Do It Effectively, https://www.forbes.com/sites/womensmedia/2020/01/08/the-most-critical-reason-you-need-to-negotiate-how-to-do-it-effectively/?sh=5d3c63530ed5.” Accessed August 30, 2022.
This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.