How to reach the top 1% of MLOps Engineers
Four moves, straight from how the highest-paid in this field use AI in 2026:
MLOps Engineer Salary in 2026
MLOps Engineer pay, in real terms
At the national median of $145,000/year, a mlops engineer earns $12,083/month before taxes. Over a 30-year career that's roughly $4,350,000 in gross earnings — and that's before raises, promotions, or bonuses.
That puts this role about 202% above the U.S. median wage for all workers (about $48,060/year, per BLS). Using the common rule of keeping housing under 30% of gross pay, this salary supports about $3,625/month in rent or mortgage.
Figures are gross (pre-tax) estimates from the national median; use the take-home and hourly calculators on PayCrunch for your exact state and situation.
What Does a MLOps Engineer Do?
MLOps engineers build and maintain the infrastructure that deploys, monitors, and manages machine learning models in production.
MLOps Engineer Salary by State
Select your state to see the adjusted mlops engineer salary based on cost-of-living differences.
How to Become a MLOps Engineer
Education: Bachelor's degree in CS or related
Certifications: AWS/GCP ML certifications
MLOps Engineer Salary by Experience
Estimates based on BLS percentile data and industry surveys. Actual salaries vary by employer, location, and individual qualifications.
Top 10 Highest-Paying States for MLOps Engineers
| # | State | Annual | Monthly | Hourly |
|---|---|---|---|---|
| 1 | Hawaii | $171,100 | $14,258 | $82.26 |
| 2 | California | $166,750 | $13,896 | $80.17 |
| 3 | New York | $166,750 | $13,896 | $80.17 |
| 4 | Massachusetts | $162,400 | $13,533 | $78.08 |
| 5 | New Jersey | $162,400 | $13,533 | $78.08 |
| 6 | Connecticut | $159,500 | $13,292 | $76.68 |
| 7 | Washington | $159,500 | $13,292 | $76.68 |
| 8 | Maryland | $156,600 | $13,050 | $75.29 |
| 9 | Alaska | $152,250 | $12,688 | $73.20 |
| 10 | Colorado | $152,250 | $12,688 | $73.20 |
State salaries estimated using BLS national median adjusted by regional cost-of-living factors.
Compare to Related Jobs
| Job Title | Median Salary | Hourly | Difference |
|---|---|---|---|
| MLOps Engineer | $145,000 | $69.71 | — |
| Application Architect | $145,000 | $69.71 | — |
| Natural Language Processing Engineer | $145,000 | $69.71 | — |
| Solutions Architect | $142,000 | $68.27 | $-3,000 |
| Computer Vision Engineer | $142,000 | $68.27 | $-3,000 |
| Site Reliability Engineer | $140,000 | $67.31 | $-5,000 |
| Platform Engineer | $140,000 | $67.31 | $-5,000 |
Job Outlook
The BLS projects +30% growth for mlops engineers through 2032, which is much faster than average compared to the average for all occupations (3%).
🆕 New & Trending AI Tools for MLOps EngineerReviewed July 2026
We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for MLOps Engineer work right now.
Terminal coding agent that reads your repo, runs tests, and ships multi-file changes.
How a MLOps Engineer uses it: describe a feature and let it implement and test it across the codebase
Agent that runs longer, deterministic multi-step coding jobs on its own.
How a MLOps Engineer uses it: delegate a well-defined build or migration and review the finished result
Agentic IDE that keeps context across a whole project.
How a MLOps Engineer uses it: make large, coordinated changes without losing track of the codebase
Spec-driven coding agent that turns written specs into working code.
How a MLOps Engineer uses it: write the spec first and let it build to that spec
Google tool that answers questions grounded only in the documents you give it — with citations.
How a MLOps Engineer uses it: load your own manuals, policies, or PDFs and ask questions that stay accurate to the source
AI-native code editor that edits across an entire project.
How a MLOps Engineer uses it: describe a change in plain English and let it rewrite and refactor whole files
AI pair-programmer built into VS Code and GitHub that now completes multi-step tasks.
How a MLOps Engineer uses it: hand off a task and have it plan, edit multiple files, and open a pull request
The most-used AI assistant — writing, analysis, research, and images from a plain-language chat.
How a MLOps Engineer uses it: draft emails and documents, summarize long files, and get instant answers to on-the-job questions
AI assistant known for careful writing, long-document analysis, and coding.
How a MLOps Engineer uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing
Frequently Asked Questions
Methodology and data sources
Salary data is based on the Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics (OES) program. National median, 10th percentile, and 90th percentile figures are sourced from the most recent BLS OES release. State-level salary estimates are calculated by applying regional price parity adjustments from the Bureau of Economic Analysis (BEA) to the national median. Job growth projections are from the BLS Employment Projections program. Education and certification requirements are based on BLS Occupational Outlook Handbook descriptions. All figures are approximate and updated periodically.