Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Artificial intelligence jobs have been hot in Silicon Valley and elsewhere, with a machine-learning engineer getting an average salary of $142,858 a year. But AI job-posting growth has slowed, and interest in these jobs is also dipping, according to a study by job site Indeed.
AI job postings on Indeed rose 29.1% from May 2018 to May 2019. However, that increase is substantially less than it was the previous two years. During the same time period — May 2017 to May 2018 — AI job postings on Indeed rose 57.9%, and a whopping 136.2% between May 2016 and May 2017.
Meanwhile, interest from job seekers is leveling off. From May 2018 to 2019, searches for AI-related jobs on Indeed decreased 14.5%. By comparison, searches increased 31.9% between May 2017 and 2018 and 49.12% between May 2016 and 2017. This year’s drop also suggests there could be more open jobs than qualified workers to fill them, Indeed said.
AI job searches don’t always keep pace with the number of postings. Consider data scientists, whose job is to take raw data and apply programming, visualizations, and statistical modeling to extract actionable insights for organizations.
The AI Impact Tour
Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you!
Given that data is “the new oil,” data scientists are in high demand, and Indeed’s research shows job postings jumped 31% from 2017 to 2018. During the same period, however, job searches only increased about 14%.
Machine learning and deep learning engineers rule the top 10 AI jobs list
To learn about the most sought-after AI jobs posted on Indeed between 2018 and 2019, the firm’s analytics team identified 10 positions with the highest percentage of job descriptions that include the keywords “artificial intelligence” or “machine learning.”
Top 10 AI jobs
- machine learning engineer
- deep learning engineer
- senior data scientist
- computer vision engineer
- data scientist
- algorithm developer
- junior data scientist
- developer consultant
- director of data science
- lead data scientist
Director of analytics, statistician, principal scientist, computer scientist, research engineer, and data engineer are former contenders that didn’t make the top 10 this year.
Indeed discovered that machine learning engineer job postings had the highest percentage of AI and machine learning keywords this year (as was true in 2018). Machine learning engineers develop devices and software that use predictive technology, such as Apple’s Siri or weather-forecasting apps. They ensure machine learning algorithms have the data that needs to be processed and analyze huge amounts of real-time data to make machine learning models more accurate.
While machine learning engineer jobs still have the largest number of postings containing relevant keywords, in 2018 they comprised a greater percentage of these postings (94.2%, versus 75% in 2019).
Many of the jobs requiring AI skills on 2019’s top 10 were nowhere to be found on 2018’s list — such as deep learning engineer, appearing for the first time in second place. Deep learning engineers develop programming systems that mimic brain functions, among other tasks.
These engineers are key players in three rapidly growing fields: autonomous driving, facial recognition, and robotics. The global facial recognition market alone is poised to grow from $3.37 billion in 2016 to $7.76 billion by 2022, according to one study.
The year-over-year differences could reflect the growing demand for data scientists at all types of companies; many employers now need a whole data science team, with staff from junior to director levels. By comparison, the 2018 list contained data science jobs that were more generic, such as data scientist, principal scientist, and computer scientist. Hiring for a range of experience levels appeals to a wider swathe of talent, which can help organizations better compete in the tight labor market, Indeed said.
Top AI jobs by average salary
Machine learning engineer is not only the top AI job in terms of the number of job postings, it also commands one of the highest paychecks. And it’s the role with the biggest boost in average annual salary, as compared to 2018.
Machine learning engineer is the third-highest paying job on Indeed’s 2018 and 2019 rankings. This year, however, the average annual salary for this position is $142,859, which is $8,409 higher than last year’s. That’s an increase of 5.8%, compared to the average 2.9% salary increase that human resources firm Mercer predicted for 2019.
Similarly, an algorithm engineer’s average annual salary rose to $109,313 this year — an increase of $5,201, or 4.99%. Both salary bumps are likely a result of organizations spending more to attract talent to these crucial roles in a competitive AI job market.
As with the previous list, the positions that top the salary rankings show an evolution and maturation of the overall AI market. More generalized positions, such as director of analytics, data engineer, computer scientist, statistician, and research engineer, were all on 2018’s list but didn’t crack the top 10 this year. New positions taking their place on the 2019 list include more differentiated data science jobs, such as senior data scientist and lead data scientist.
New York and San Francisco lead top cities for AI jobs
Compared to last year, 2019’s ranking of metropolitan areas with the largest percentages of AI jobs hasn’t changed significantly — though there are a few shifts, as well as a newcomer.
Top Cities for AI Jobs
- New York, New York
- San Francisco, California
- Washington, DC
- San Jose, California
- Seattle, Washington
- Boston, Massachusetts
- Los Angeles, California
- Chicago, Illinois
- Dallas-Fort Worth, Texas
- Atlanta, Georgia
In both 2018 and 2019, the New York City and San Francisco metro areas ranked first and second, respectively. However, New York has lost some of its edge: Last year, the Big Apple comprised 11.6% of AI job postings, which dipped to 9.72% in 2019. By comparison, San Francisco had a 9.6% share in 2018; this dropped to 9.20% in 2019, but it’s now only slightly behind New York. (San Francisco also ranks second on Indeed’s Best Cities for Job Seekers 2019 list, out of 25 metro areas.)
New York’s top position is surprising, but the city is home to diverse industries, from financial services to publishing — many of which are now adopting AI. Many West Coast-based tech companies (such as Amazon, Facebook, and Google) have a significant presence in the region. And New York has its share of AI-related tech startups, such as AlphaSense, Clarifai, Persado, and x.ai.
Three areas swapped positions on Indeed’s lists between last year and 2019. In 2018, San Jose ranked third (9.2%) and Washington, D.C. fourth (7.9%). But this year, D.C. ranks third, while San Jose is fourth. In 2019, Boston (slipping from fifth place) traded places with Seattle (rising from sixth), and Chicago ceded its seventh-place position to Los Angeles (formerly eighth). Dallas-Fort Worth held onto ninth place. And Philadelphia, at number 10 last year, was bumped off the chart by newcomer Atlanta.
Will AI create more jobs than it eliminates?
In the coming years, the big question will be whether AI generates more jobs than it eliminates.
Some studies suggest AI will, in fact, produce more jobs than it destroys. The 2018 “Future of Jobs” report from the World Economic Forum finds that by 2022, a shift in the division of labor between humans and machines — or AI-enabled automation — will displace 75 million jobs but generate 133 million new ones. Gartner estimates AI will create 2.3 million new jobs in 2020 while eliminating 1.8 million positions. And according to a 2019 Dun & Bradstreet report, 40% of organizations are adding more jobs as a result of adopting AI, while only 8% are cutting jobs because of the new technology. We’ll have to wait to see if that trend holds.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.