2026 Salary Guide
Llm Ops

MLOps Engineer Salary in 2026

MLOps Engineers own the infrastructure and tooling that takes ML models from experimentation to reliable, monitored production services. Expertise in Kubernetes, feature stores, and model registries is highly valued.

Quick answer: A senior MLOps Engineer in the US earns a median base salary of $200k in 2026, with a typical range of $170k$248k. Total compensation including equity is often 30–80% higher.

MLOps Engineer Salary by Experience Level

US base salary ranges, 2026. Excludes equity, bonuses, and benefits.

LevelLowMedianHigh
Junior (0–2 yrs)$100k$118k$140k
Mid-level (3–5 yrs)$135k$158k$190k
Senior (6–9 yrs)Benchmark$170k$200k$248k
Staff / Principal (10+ yrs)$218k$262k$330k

MLOps Engineer Salary by Location

Estimated senior-level base salary. Multipliers applied to US median of $200k.

LocationEstimated Median
San Francisco$230k
New York$220k
Seattle$216k
Remote (US)Baseline$200k
London$150k
Berlin$140k
Toronto$156k
Singapore$160k
India$60k

Location adjustments reflect cost-of-living differences, local talent supply, and typical employer pay scales for that market. Remote US roles benchmark at 1.0×.

MLOps Engineer Salary — FAQ

How much does a MLOps Engineer make?

A MLOps Engineer in the US earns between $100k (entry-level) and $330k (staff/principal) in base salary in 2026. The median across all experience levels is approximately $185k.

What is a senior MLOps Engineer salary?

A senior MLOps Engineer with 6–9 years of experience earns $170k$248k in base, with a median of $200k. In San Francisco or at a top AI lab, total compensation (base + equity + bonus) can easily exceed $340k.

Is MLOps Engineer a high-paying career?

Yes — MLOps Engineer is consistently one of the highest-compensated technical roles in the software industry. Demand significantly outpaces supply, which keeps salaries elevated and gives experienced practitioners strong negotiating leverage.

How do I increase my MLOps Engineer salary?

The highest salary jumps come from: (1) moving to a frontier AI lab or well-funded startup, (2) developing deep specialization in high-demand sub-skills, (3) publishing research or open-source projects that raise your market profile, and (4) negotiating equity as a significant part of your package.

Find open MLOps Engineer positions

Browse current MLOps Engineer job listings across companies big and small.

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