The number of roles in Asia-Pacific made up 8% of total machine learning jobs – up from 0% in the same quarter last year.
That was followed by North America, which saw a 5.4 year-on-year percentage point change in machine learning roles.
The figures are compiled by GlobalData, which tracks the number of new job postings from key companies in various sectors over time. Using textual analysis, these job advertisements are then classified thematically.
GlobalData's thematic approach to sector activity seeks to group key company information by topic to see which companies are best placed to weather the disruptions coming to their industries.
These key themes, which include machine learning, are chosen to cover "any issue that keeps a CEO awake at night".
Tracking across job advertisements shows which companies are leading the way on specific issues and which are dragging their heels – and importantly, where the market is expanding and contracting.
Which countries are seeing the most growth for machine learning roles in the apparel industry?
The fastest-growing country was Italy, which saw zero 0% of all machine learning job adverts in the three months ending October last year, increasing to 6% in the three months ending October this year.
That was followed by China (up four percentage points), India (up two), and Belgium (up two).
The top country for machine learning roles in the apparel industry is the United States which saw 68% of all roles in the three months ending October.
Which cities are the biggest hubs for machine learning workers in the apparel industry?
Some 22% of all apparel industry machine learning roles were advertised in San Francisco (US) in the three months ending October – more than any other city.
That was followed by Portland (US) with 22% Paris (France) with 6%, and Milan (Italy) also with 6%.
A project focused on developing AI and machine learning to automate factory planning by Pennine Weavers is among the 12 successful projects that will benefit from Future Fashion Factory’s fourth innovation funding call.