Federated Learning Engineer Salary.
Across 83 U.S. cities.
$188,000
national median salary
$140,000 to $248,000. Last updated April 2026.
Highest Paying
$267,000
San Jose, CA
Best Purchasing Power
$196,000
Boston, MA
Lowest Paying
$150,000
Charleston, WV
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 Federated Learning Engineer salary in the United States is $188,000 in 2026, with the full range spanning $140,000 at the 25th percentile to $248,000 at the 75th. San Jose pays the most at $267,000, while Boston offers the best purchasing power after cost-of-living adjustments. This privacy-preserving AI specialization commands premiums driven by regulatory demand and technical complexity.
Federated Learning Engineer salary by city
Skills that increase Federated Learning Engineer pay
The skills below command measurable salary premiums for Federated Learning Engineers based on job posting data. Learning the top skill here could add $26,320 to your annual compensation.
≈ +$26,320 per year
≈ +$24,440 per year
≈ +$22,560 per year
≈ +$20,680 per year
≈ +$20,680 per year
≈ +$18,800 per year
≈ +$18,800 per year
≈ +$16,920 per year
What you should know
This privacy-preserving AI specialization commands premiums driven by regulatory demand and technical complexity. Engineers with production federated learning deployments across healthcare, finance, or telecommunications earn 15 to 22% more than general ML engineers. Expertise in secure aggregation protocols, differential privacy mechanisms, and communication-efficient training across distributed nodes significantly increases market value.
ML engineers or privacy engineers earning $115,000 to $155,000 specialize into federated learning at $140,000 to $248,000. Senior federated learning engineers earn $195,000 to $270,000 before advancing to Principal Privacy ML Engineer or Head of Privacy-Preserving AI at $230,000 to $300,000.
Total packages range from $220,000 to $420,000 with equity, privacy compliance bonuses, and research incentives of 12 to 22% of base. Healthcare and financial services companies offer the strongest total compensation due to strict data privacy requirements driving federated learning adoption.