Pay by Role
United States · Salary comparison

Data Engineer vs Machine Learning Engineer salary

In United States, a machine learning engineer earns about 19% more than a data engineer $180,000 vs $151,000 per year.

Showing amounts in USD (USD default). FX as of Mon, 13 Jul 2026 00:02:31 +0000. Convert currencies

Technology
Data Engineer
$151,000/yr
Monthly
$12,600
Hourly
$73
Range
$96,600$217,400
10-yr outlook
+30%
Pays more
Technology
Machine Learning Engineer
$180,000/yr
Monthly
$15,000
Hourly
$87
Range
$107,100$269,100
10-yr outlook
+40%

Pay range, side by side

PercentileData EngineerMachine Learning Engineer
Entry (10th)$96,600$107,100
25th$123,800$143,600
Median$151,000$180,000
75th$184,200$224,600
Senior (90th)$217,400$269,100

National United States figures in USD. Individual pay varies with experience, employer, and location.

More Technology comparisons

Frequently asked questions

Does a data engineer or machine learning engineer earn more in United States?
A machine learning engineer earns more, at about $180,000 per year vs $151,000 for a data engineer — roughly 19% ($29,000) more.
What is the salary range for these roles in United States?
A data engineer typically earns $96,600–$217,400, while a machine learning engineer earns $107,100–$269,100 per year.
How much do these jobs pay per month in United States?
On a monthly basis before tax, a data engineer averages about $12,600 and a machine learning engineer about $15,000.
How do entry-level salaries compare?
At the 10th percentile in United States, a data engineer earns about $96,600 while a machine learning engineer earns about $107,100 per year.
How do senior-level salaries compare?
At the 90th percentile in United States, a data engineer earns about $217,400 while a machine learning engineer earns about $269,100 per year.
Are data engineer and machine learning engineer similar careers?
Both roles sit in the Technology category on Pay by Role, which is why we compare them head-to-head. Day-to-day work still differs — review each job page for skills and outlook.