Data Pipeline Engineer (ML) Salary.
Across 30 U.S. cities.
$158,000
national median salary
$120,000 to $208,000. Last updated April 2026.
Highest Paying
$222,000
San Francisco, CA
Best Purchasing Power
$165,000
Phoenix, AZ
Lowest Paying
$137,000
Detroit, MI
Salary data sourced from SEC filings, H-1B Labor Condition Applications (DOL), Bureau of Labor Statistics Occupational Employment and Wage Statistics, and aggregated job postings across 50+ platforms. Ranges reflect 25th to 75th percentile for full-time positions. Cost-of-living adjustments use Bureau of Economic Analysis Regional Price Parities (2025 index). Last updated April 2026.
The average Data Pipeline Engineer (ML) salary in the United States is $158,000 in 2026, with the full range spanning $120,000 at the 25th percentile to $208,000 at the 75th. San Francisco pays the most at $222,000, while Phoenix offers the best purchasing power after cost-of-living adjustments. ML data pipeline engineers earn salaries based on the scale and complexity of data systems they build and maintain.
Data Pipeline Engineer (ML) salary by city
What you should know
ML data pipeline engineers earn salaries based on the scale and complexity of data systems they build and maintain. Engineers handling petabyte-scale training data pipelines for large model training earn 15 to 25% more than those working with smaller datasets. Experience with both batch and streaming architectures is a consistent salary booster across employers.
Junior ML pipeline engineers start at $120,000 to $142,000. Mid-level engineers managing production ML data flows earn $158,000 to $208,000. Senior engineers and infrastructure leads reach $215,000 to $280,000, while staff engineers designing organization-wide ML data platforms can command $290,000 to $370,000.
Tech companies offer equity grants of 15 to 25% of base salary with standard four-year vesting schedules. Annual performance bonuses range from 10 to 18%. On-call compensation for production pipeline maintenance adds $8,000 to $18,000 annually at some organizations.