Federated Learning Engineer Salary.
Across 81 U.S. cities.
$133,000
national median salary
$99,000 to $174,000. Last updated July 2026.
Highest Paying
$189,000
San Jose, CA
Best Purchasing Power
$139,000
Boston, MA
Lowest Paying
$106,000
Charleston, WV
Salary data sourced from Bureau of Labor Statistics Occupational Employment and Wage Statistics, H-1B Labor Condition Applications (DOL), state pay-transparency job postings, and community submissions. Most ranges are anchored to BLS OES occupation wage percentiles and placed by seniority level (entry near the 25th, mid at the median, senior at the 75th); a minority of emerging roles retain a modeled estimate where BLS has no matching series. Cost-of-living adjustments use Bureau of Economic Analysis Regional Price Parities (2025 index). Last updated July 2026. Baseline derived from BLS SOC 15-1252. Full methodology.
The average Federated Learning Engineer salary in the United States is $133,000 in 2026, with the full range spanning $99,000 at the 25th percentile to $174,000 at the 75th. San Jose pays the most at $189,000, 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 $18,620 to your annual compensation.
≈ +$18,620 per year
≈ +$17,290 per year
≈ +$15,960 per year
≈ +$14,630 per year
≈ +$14,630 per year
≈ +$13,300 per year
≈ +$13,300 per year
≈ +$11,970 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.
Total compensation breakdown.
Salary by company size
Remote salary adjustment
Remote Federated Learning Engineers typically earn $120,000 (10% less than on-site). This reflects location-adjusted pay policies at companies using geographic salary bands. Some companies pay flat national rates regardless of location.
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Common questions about Federated Learning Engineer pay.
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