PyTorch Job Trends in Milton Keynes

PyTorch
Buckinghamshire > Milton Keynes

The table below provides summary statistics and salary benchmarking for jobs advertised in Milton Keynes requiring PyTorch skills. It covers permanent job vacancies from the 6 months leading up to 14 December 2025, with comparisons to the same periods in the previous two years.

6 months to
14 Dec 2025
Same period 2024 Same period 2023
Rank 52 - -
Rank change year-on-year - - -
Permanent jobs citing PyTorch 1 0 0
As % of all permanent jobs in Milton Keynes 0.21% - -
As % of the Libraries, Frameworks & Software Standards category 1.54% - -
Number of salaries quoted 1 0 0
Median annual salary (50th Percentile) £55,000 - -
Buckinghamshire median annual salary £55,000 - -

All Software Libraries and Frameworks
Milton Keynes

PyTorch falls under the Software Libraries and Frameworks category. For comparison with the information above, the following table provides summary statistics for all permanent job vacancies requiring technical specification, industry standards, software libraries and framework skills in Milton Keynes.

Permanent vacancies with a requirement for technical specification, industry standards, software libraries and framework skills 65 70 113
As % of all permanent jobs advertised in Milton Keynes 13.43% 17.95% 22.11%
Number of salaries quoted 60 53 96
10th Percentile £37,500 £37,750 £46,050
25th Percentile £46,875 £46,250 £47,500
Median annual salary (50th Percentile) £57,750 £55,000 £60,000
Median % change year-on-year +5.00% -8.33% +5.26%
75th Percentile £67,500 £60,000 £77,500
90th Percentile £73,875 £62,500 £88,750
Buckinghamshire median annual salary £55,000 £55,000 £60,000
% change year-on-year - -8.33% -

PyTorch
Job Vacancy Trend in Milton Keynes

Historical trend showing the proportion of permanent IT job postings citing PyTorch relative to all permanent IT jobs advertised in Milton Keynes.

PyTorch job vacancy trend in Milton Keynes

PyTorch
Co-Occurring Skills & Capabilities in Milton Keynes 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:

Job Titles
1 1 (100.00%) Data Scientist
Libraries, Frameworks & Software Standards
1 1 (100.00%) NumPy
1 1 (100.00%) Pandas
1 1 (100.00%) scikit-learn
Processes & Methodologies
1 1 (100.00%) Data Science
1 1 (100.00%) Machine Learning
1 1 (100.00%) Performance Engineering
1 1 (100.00%) Software Engineering
Programming Languages
1 1 (100.00%) Python