MLOps Team Cost Calculator (MLOps Engineer Salary + Burden)
Add up what an MLOps team really costs. Enter headcount and base salary for each role, a benefits burden and any tooling spend; the calculator returns the fully loaded annual cost, cost per head and monthly run-rate. Salary defaults are U.S. Bureau of Labor Statistics May 2025 mean wages for the nearest published occupation, not a guess at an MLOps title — overwrite them with your own offers.
An MLOps team cost is the fully loaded yearly expense of the people who build, ship and run machine-learning systems: base salaries, the employer's benefits and payroll burden on top of them, and the tools they need. This calculator multiplies headcount by salary for four roles, adds a burden percentage you control, and reports cost per head and a monthly run-rate.
MLOps engineer salary: what public data exists
There is no official "MLOps engineer" occupation. The U.S. Bureau of Labor Statistics (BLS) publishes wages by Standard Occupational Classification code, and MLOps, ML engineering and data engineering work is spread across several codes. The table shows the May 2025 national figures for the closest ones. The calculator pre-fills the mean wage of the nearest code for each role; replace them with your real offers, because a senior hire in a high-cost city can sit well above a national mean.
| BLS occupation (SOC code) | Mean annual wage, May 2025 | Used as default for |
|---|---|---|
| Software developers (15-1252) | $148,100 | ML engineer, MLOps engineer |
| Database architects (15-1243) | $144,440 | Data engineer |
| Information security analysts (15-1212) | $132,510 | AI security engineer |
| Data scientists (15-2051) | $126,800 | Reference only |
| Computer and information research scientists (15-1221) | $153,930 | Reference only |
| Network and computer systems administrators (15-1244) | $103,680 | Reference only |
How the benefits burden is calculated
The default burden of 42.9% comes from the BLS Employer Costs for Employee Compensation release for June 2026. For private-industry workers, wages and salaries averaged $32.82 per hour worked and benefits averaged $14.07, so benefits equal 42.9% of wages (30.0% of total compensation). That benefits figure covers paid leave, supplemental pay, insurance, retirement and legally required benefits such as Social Security and unemployment insurance. It does not include equity, recruiting or workspace.
Worked example: a six-person MLOps team
With the defaults, 3 ML engineers at $148,100, 2 data engineers at $144,440 and 1 MLOps engineer at $148,100 come to $881,280 of base salary. A 42.9% burden adds $378,069.12, giving a total annual cost of $1,259,349.12, or $209,891.52 per head and $104,945.76 a month. Add a yearly tooling and cloud budget in the last field to include it in the total and the run-rate.
What this estimate leaves out
The result is a planning number for U.S. employees. It does not model equity compensation, bonuses, contractor rates, hiring ramp or location pay bands. The BLS wages are national means for broad occupations, measured in May 2025; no 2027 wage survey exists yet, so treat the year in the page address as the planning year, not the data year.
Sources: BLS Occupational Employment and Wage Statistics, May 2025 (series read from the BLS public data API); BLS Employer Costs for Employee Compensation, June 2026. Last updated: October 2026.