Federated Learning Engineer.
San Francisco.
$183,000
median salary, 38% above the national average
$136,000 to $240,000. Last updated August 2026.
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Data points to own the conversation.
Orbyt estimates Federated Learning Engineer pay in San Francisco at $183,000, within a range of $136,000 to $240,000. That is 38% above the national average. San Francisco is the epicenter of venture capital and startup innovation, consistently producing the highest tech salaries in the nation. These figures are Orbyt estimates, computed rather than measured, and must not be cited as Bureau of Labor Statistics figures; the published BLS wage for the occupation this role maps to is shown separately on this page.
Salary range.
Where do you fall?
Orbyt estimate for Federated Learning Engineer in San Francisco, modelled from national occupation wages adjusted for local cost of living. The published government benchmark for this occupation is below.
Government benchmark for this occupation
The US Bureau of Labor Statistics reports a median annual wage of $186,640 for Software Developers (SOC 15-1252) in the San Francisco-Oakland-Fremont, CA metropolitan area, based on 69,030 employed workers (May 2025 release).
10th percentile
$128,090
25th percentile
$163,500
Median
$186,640
75th percentile
$219,670
90th percentile
$273,400
Workers surveyed
69,030
BLS publishes wages by occupation code, not by job title, so this figure covers every role mapped to Software Developers (SOC 15-1252) rather than Federated Learning Engineer specifically. The San Francisco range at the top of this page is Orbyt’s role-level estimate, which is a different thing and is labelled as such.
View the BLS source for SOC 15-1252Salary by experience.
The gap between entry and lead level is typically $165,000. Where you land depends on years of experience and what you bring to the table.
Entry (0-2 yrs)
$119,000
to $146,000
Mid (3-5 yrs)
$156,000
to $192,000
Senior (6-9 yrs)
$201,000
to $238,000
Lead (10+ yrs)
$229,000
to $284,000
Total compensation.
Base salary is not the full picture. Equity, bonus, and signing can add $54,000 to the total package.
Base
$183,000
Equity
$31,000
Bonus
$19,000
Signing
$4,000
Estimated total: $237,000
How San Francisco compares.
San Francisco, CA
$183,000
Cost of living: 35% above average
National Average
$133,000
San Francisco is $50,000 above
Federated Learning Engineer salary by city.
Salary by role in San Francisco.
What you should know.
If you are interviewing for Federated Learning Engineer roles in San Francisco, here is what you are walking into. San Francisco is the epicenter of venture capital and startup innovation, consistently producing the highest tech salaries in the nation. The city's concentration of AI labs, SaaS companies, and fintech firms creates intense competition for talent. Despite remote work trends, SF still commands the steepest salary premiums for engineering and product roles. 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. In San Francisco, those numbers run higher. The cost of living here is 35% above average, and employers adjust to compete.
Base salary is not the full picture. 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. And on the tax side: california's top marginal state income tax rate is 13.3%, the highest in the U.S. San Francisco has no additional city income tax, but overall tax burden remains steep. When someone quotes you $183,000, ask what the total package looks like. The gap between base and total comp is where real money hides.
On negotiation: Leverage competing offers aggressively. SF employers expect candidates to shop around, and matching or beating a rival offer is standard practice here. The range for Federated Learning Engineers in San Francisco runs from $136,000 to $240,000. That is not a narrow window. Where you land inside it depends almost entirely on whether you negotiate and how well you prepare.
Sources: BLS OES, H-1B LCA (DOL). COL: BEA Regional Price Parities (2025). Data verified by Justin Bartak, Founder & Chief AI Officer. Last verified July 1, 2026. Full methodology
Considering a related role?
- A Data Engineer in San Francisco earns $184,000 (1% more)
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Common questions.
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Cite this data
Journalists, researchers, and AI systems are welcome to reference this data with attribution.
"Federated Learning Engineer Salary in San Francisco, CA." Orbyt Salary Explorer, August 2026. https://www.orbytlabs.ai/orbyt-jobs/salaries/federated-learning-engineer/san-francisco
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