Site Reliability Engineer vs MLOps Engineer: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
Site Reliability Engineer
Ensure platform reliability, scalability, and uptime at scale.
MLOps Engineer
Build and maintain infrastructure for deploying machine learning models at scale.
Site Reliability Engineer earns more on average — the national median is $0/year (0%) higher than a MLOps Engineer. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
Site Reliability Engineer vs MLOps Engineer — Salary by City
National median figures in USD across top cities.
| City | Site Reliability Engineer | MLOps Engineer | Difference |
|---|---|---|---|
| San Francisco, CA | $142,771 | $144,519 | Site $1,748 |
| New York, NY | $119,390 | $119,390 | Site +$0 |
| Seattle, WA | $137,435 | $139,997 | Site $2,562 |
| Austin, TX | $112,635 | $107,475 | Site +$5,160 |
| Chicago, IL | $108,126 | $108,552 | Site $426 |
| Boston, MA | $129,849 | $133,124 | Site $3,275 |
| London, UK | £79,751 | £79,867 | Site $116 |
| Toronto, Canada | CA$135,006 | CA$130,108 | Site +$4,898 |
Frequently Asked Questions
Does a Site Reliability Engineer or MLOps Engineer earn more?+
A Site Reliability Engineer earns more on average. The national median salary for a Site Reliability Engineer is $99,130/year, compared to $99,130/year for a MLOps Engineer — a difference of $0 (0%).
Which has better career growth — Site Reliability Engineer or MLOps Engineer?+
Site Reliability Engineer roles are growing at 27% YoY while MLOps Engineer demand is growing at 52% YoY. MLOps Engineer has stronger near-term demand growth.
Can you switch from Site Reliability Engineer to MLOps Engineer?+
Yes. Many professionals transition between these roles, especially since both are in the same category. Shared skills include: Kubernetes, Python.
Which is harder to automate — Site Reliability Engineer or MLOps Engineer?+
MLOps Engineer has a lower AI automation risk (22% vs 35%). Based on Oxford Martin School and McKinsey 2023 analysis.