Average MLOps Engineer Salary

$130k – $175k at mid-level to $155k – $220k at senior level in the US, depending on experience and location.

MLOps engineer salary in the US typically ranges from $130k to $220k for mid and senior levels, with staff and principal roles reaching $185k–$270k+. MLOps salary reflects demand for ML pipelines, model serving, and the infrastructure that powers production AI and LLM systems.

Salary by level for MLOps engineers varies with experience in ML platforms, feature stores, and production ML. The table below shows typical MLOps engineer pay by experience so you can benchmark your role or offers.

MLOps Engineer salary by level

Level	Typical range (US)
Mid-level	$130k – $175k
Senior	$155k – $220k
Staff / Principal	$185k – $270k+

Sources: Levels.fyi, Glassdoor, LinkedIn Salary Insights (aggregated US base salary ranges, 2025–2026).

What affects MLOps Engineer salary?

MLOps engineer salary is driven by experience with ML pipelines and production ML, location and industry (AI/ML-heavy companies pay a premium), company stage, and skills in Kubeflow, MLflow, SageMaker/Vertex AI, and GPU infrastructure. Demand has increased sharply with LLM and AI adoption.

Remote vs on-site pay

US-based remote roles for cloud operations typically pay within 2–5% of the national average. Some companies apply location-based adjustments, but the gap has narrowed. High-demand roles in SRE and platform engineering often match or exceed on-site compensation.

Certifications that can boost pay

AWS Certified Machine Learning – SpecialtyValidates design and implementation of ML solutions on AWS.
Google Professional ML EngineerCovers deploying and maintaining ML models on GCP.
Azure AI Engineer AssociateMicrosoft certification for building and managing AI solutions on Azure.