By AI Trends Staff
The job site Indeed recently published an update its report on the top 10 AI jobs and salaries. Here are some highlights:
Postings for jobs in artificial intelligence (AI) rose 29% in the last year, from May 2018 to May 2019, according to an account summarizing the results in TechRepublic. However, this represents a slowing of the growth rate: From May 2017 to May 2018, AI job postings on the site grew nearly 58%, and from May 2016 to May 2017, they grew 136%.
Job seeker interest in AI-related positions is also beginning to slow, Indeed researchers noted in a Friday blog post: Searches for AI-related jobs on Indeed decreased by nearly 15% in the last year, while they had increased 32% and 49% the previous two years. The drop suggests there may be more open jobs than there are qualified employees to fill them, the post noted.
The following 10 positions are the most in-demand AI jobs, with the highest percentage of job descriptions that included the keywords “artificial intelligence” or “machine learning,” according to Indeed:
- 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
Some job titles are being seen on the list for the first time. For example, deep learning engineer is new to the list. Also new: senior and junior data scientist, developer consultant, director of data science, and lead data scientists.
Other job titles are dropping off the list from last year. Not mentioned in 2019 were: director of analytics, statistician, principal scientist, and data engineer.
These year-over-year changes could be a sign of growing demand for data scientists across all companies and industries, the post noted. While the 2018 list contained data science jobs with more generic titles, 2019’s list suggests that companies are seeking out data science teams with different experience levels and skill sets.
In salary highlights, open jobs outnumber the number of qualified candidates to fill them, driving up salaries, as Tech Republic reported.
Machine learning engineers are the most in-demand AI job based on the number of job postings, and also are offered the highest paycheck on average. They are also the professionals with the largest boost in salary year over year, the data showed.
Here are the five AI job titles with the highest salaries, according to Indeed:
- Machine learning engineer
Average salary: $142,859
- Data scientist
Average salary: $126,927
- Computer vision engineer
Average salary: $126,400
- Data warehouse architect
Average salary: $126,008
- Algorithm engineer
Average salary: $109,313
Machine learning engineers were the third-highest paying job in Indeed’s previous two rankings. This year, the position jumped in salary $8,409 over last year, or 5.8%, bringing it to the no. 1 spot. Algorithm engineer salaries also jumped $5,201 or about 5% over last year. Both of these increases are likely a result of companies spending more to attract talent to these roles in a competitive tech jobs market, Indeed noted.
The best cities for finding an AI job based on the number of open positions were New York, San Francisco, and Washington, D.C., according to Indeed.
To explain the leveling off of candidate-initiated searches for AI and machine learning jobs, Forbes cited broader adoption and maturing in organizations, leading to a greater variety of skills being recruited for. The 14.5% reduction reflects the broadening base of skills enterprises need to get the most out of AI and machine learning.
From a supply side, potential job candidates are seeing the broadening base of skills they need to get hired, which are quickly making job descriptions from two years ago or longer obsolete. Finding candidates who have capabilities and potential to excel in AI and machine learning positions needs to get beyond just relying on job descriptions.
Among startups positioning to help match candidates to jobs, is Eightfold.ai, which is matching candidates with the optimal set of capabilities for open positions using a machine learning algorithm.