Network 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.
Network Engineer
Design, implement, and manage computer network infrastructure.
MLOps Engineer
Build and maintain infrastructure for deploying machine learning models at scale.
Network Engineer earns more on average — the national median is $34,920/year (35%) higher than a MLOps Engineer. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
Network Engineer vs MLOps Engineer — Salary by City
National median figures in USD across top cities.
| City | Network Engineer | MLOps Engineer | Difference |
|---|---|---|---|
| San Francisco, CA | $195,491 | $144,519 | Network +$50,972 |
| New York, NY | $165,772 | $119,390 | Network +$46,382 |
| Seattle, WA | $192,889 | $139,997 | Network +$52,892 |
| Austin, TX | $149,704 | $107,475 | Network +$42,229 |
| Chicago, IL | $145,221 | $108,552 | Network +$36,669 |
| Boston, MA | $176,955 | $133,124 | Network +$43,831 |
| London, UK | £106,873 | £79,867 | Network +$27,006 |
| Toronto, Canada | CA$177,211 | CA$130,108 | Network +$47,103 |
Frequently Asked Questions
Does a Network Engineer or MLOps Engineer earn more?+
A Network Engineer earns more on average. The national median salary for a Network Engineer is $134,050/year, compared to $99,130/year for a MLOps Engineer — a difference of $34,920 (35%).
Which has better career growth — Network Engineer or MLOps Engineer?+
Network Engineer roles are growing at 6% YoY while MLOps Engineer demand is growing at 52% YoY. MLOps Engineer has stronger near-term demand growth.
Can you switch from Network Engineer 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 — Network Engineer or MLOps Engineer?+
MLOps Engineer has a lower AI automation risk (22% vs 52%). Based on Oxford Martin School and McKinsey 2023 analysis.