Product Designer vs MLOps Engineer: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
Product Designer
Design end-to-end product experiences across digital touchpoints.
MLOps Engineer
Build and maintain infrastructure for deploying machine learning models at scale.
Product Designer earns more on average — the national median is $4,870/year (5%) higher than a MLOps Engineer. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
Product Designer vs MLOps Engineer — Salary by City
National median figures in USD across top cities.
| City | Product Designer | MLOps Engineer | Difference |
|---|---|---|---|
| San Francisco, CA | $152,323 | $144,519 | Product +$7,804 |
| New York, NY | $124,352 | $119,390 | Product +$4,962 |
| Seattle, WA | $152,056 | $139,997 | Product +$12,059 |
| Austin, TX | $119,558 | $107,475 | Product +$12,083 |
| Chicago, IL | $109,818 | $108,552 | Product +$1,266 |
| Boston, MA | $139,034 | $133,124 | Product +$5,910 |
| London, UK | £83,576 | £79,867 | Product +$3,709 |
| Toronto, Canada | CA$134,572 | CA$130,108 | Product +$4,464 |
Frequently Asked Questions
Does a Product Designer or MLOps Engineer earn more?+
A Product Designer earns more on average. The national median salary for a Product Designer is $104,000/year, compared to $99,130/year for a MLOps Engineer — a difference of $4,870 (5%).
Which has better career growth — Product Designer or MLOps Engineer?+
Product Designer roles are growing at 22% YoY while MLOps Engineer demand is growing at 52% YoY. MLOps Engineer has stronger near-term demand growth.
Can you switch from Product Designer 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 — Product Designer or MLOps Engineer?+
MLOps Engineer has a lower AI automation risk (22% vs 36%). Based on Oxford Martin School and McKinsey 2023 analysis.