The table below provides summary statistics and salary benchmarking for jobs advertised in Salford requiring Machine Learning skills. It covers permanent job vacancies from the 6 months leading up to 13 November 2025, with comparisons to the same periods in the previous two years.
Machine Learning falls under the Processes and Methodologies category. For comparison with the information above, the following table provides summary statistics for all permanent job vacancies requiring process or methodology skills in Salford.
Permanent vacancies with a requirement for process or methodology skills
82
126
46
As % of all permanent jobs advertised in Salford
85.42%
85.14%
100.00%
Number of salaries quoted
51
40
33
10th Percentile
£26,500
£39,000
£41,250
25th Percentile
£30,750
£46,713
£43,155
Median annual salary (50th Percentile)
£42,500
£59,430
£50,000
Median % change year-on-year
-28.49%
+18.86%
-
75th Percentile
£55,000
£74,144
£61,445
90th Percentile
£77,500
£80,000
£69,800
Manchester median annual salary
£52,500
£55,000
£59,556
% change year-on-year
-4.55%
-7.65%
+8.28%
Machine Learning Job Vacancy Trend in Salford
Historical trend showing the proportion of permanent IT job postings citing Machine Learning relative to all permanent IT jobs advertised in Salford.
Machine Learning Salary Trend in Salford
Salary distribution trend for jobs in Salford citing Machine Learning.
Machine Learning Top 10 Co-Occurring Skills & Capabilities in Salford
For the 6 months to 13 November 2025, job vacancies citing Machine Learning also mentioned the following skills and capabilities in order of popularity.
The figures indicate the absolute number of co-occurrences and as a proportion of all permanent job ads across the Salford region with a requirement for Machine Learning.
Machine Learning Co-Occurring Skills & Capabilities in Salford by Category
The following tables expand on the one above by listing co-occurrences grouped by category. They cover the same employment type, locality and period, with up to 20 co-occurrences shown in each category:
