IT Support Specialist vs MLOps Engineer: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
IT Support Specialist
Provide technical support for hardware, software, and networks.
MLOps Engineer
Build and maintain infrastructure for deploying machine learning models at scale.
MLOps Engineer earns more on average — the national median is $37,270/year (60%) higher than a IT Support Specialist. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
IT Support Specialist vs MLOps Engineer — Salary by City
National median figures in USD across top cities.
| City | IT Support Specialist | MLOps Engineer | Difference |
|---|---|---|---|
| San Francisco, CA | $92,808 | $144,519 | IT $51,711 |
| New York, NY | $72,917 | $119,390 | IT $46,473 |
| Seattle, WA | $86,967 | $139,997 | IT $53,030 |
| Austin, TX | $69,244 | $107,475 | IT $38,231 |
| Chicago, IL | $64,877 | $108,552 | IT $43,675 |
| Boston, MA | $79,215 | $133,124 | IT $53,909 |
| London, UK | £47,998 | £79,867 | IT $31,869 |
| Toronto, Canada | CA$84,196 | CA$130,108 | IT $45,912 |
Frequently Asked Questions
Does a IT Support Specialist or MLOps Engineer earn more?+
A MLOps Engineer earns more on average. The national median salary for a IT Support Specialist is $61,860/year, compared to $99,130/year for a MLOps Engineer — a difference of $37,270 (60%).
Which has better career growth — IT Support Specialist or MLOps Engineer?+
IT Support Specialist roles are growing at 5% YoY while MLOps Engineer demand is growing at 52% YoY. MLOps Engineer has stronger near-term demand growth.
Can you switch from IT Support Specialist to MLOps Engineer?+
Yes. Many professionals transition between these roles, especially since both are in the same category. Shared skills include: analytical thinking, communication, and industry knowledge.
Which is harder to automate — IT Support Specialist or MLOps Engineer?+
MLOps Engineer has a lower AI automation risk (22% vs 71%). Based on Oxford Martin School and McKinsey 2023 analysis.