Federated Learning Engineer.
Virginia Beach.
$182,000
median salary, 3% below the national average
$136,000 to $241,000. Last updated April 2026.
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Data points to own the conversation.
Federated Learning Engineer pay in Virginia Beach ranges from $136,000 to $241,000 in 2026. The median is $182,000, 3% below the national average. Virginia Beach anchors the Hampton Roads region with a strong military presence, growing cybersecurity sector, and expanding tech corridor. Every dollar in that range is negotiable if you come prepared.
Salary range
Where do you fall?
Salary by experience
The gap between entry and lead level is typically $164,000. Where you land depends on years of experience and what you bring to the table.
Entry (0-2 yrs)
$118,000
to $146,000
Mid (3-5 yrs)
$155,000
to $191,000
Senior (6-9 yrs)
$200,000
to $237,000
Lead (10+ yrs)
$228,000
to $282,000
Salary trend
+3% YoYTotal compensation
Base salary is not the full picture. Equity, bonus, and signing can add $54,000 to the total package.
Base
$182,000
Equity
$31,000
Bonus
$19,000
Signing
$4,000
Estimated total: $236,000
How Virginia Beach compares
Virginia Beach, VA
$182,000
Cost of living: 2% below average
National Average
$188,000
Virginia Beach is $6,000 below
Federated Learning Engineer salary by city
Salary by role in Virginia Beach
What you should know
If you are interviewing for Federated Learning Engineer roles in Virginia Beach, here is what you are walking into. Virginia Beach anchors the Hampton Roads region with a strong military presence, growing cybersecurity sector, and expanding tech corridor. Naval Station Norfolk drives significant defense contractor employment. The lower cost of living compared to Northern Virginia attracts remote workers and military-to-civilian transitions. 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 Virginia Beach, cost of living sits near the national average, so the numbers you see are roughly what you keep.
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: virginia's flat 5.75% state income tax applies. Virginia Beach has no city income tax. The moderate rate combined with lower housing costs than Northern Virginia creates good take home pay. When someone quotes you $182,000, ask what the total package looks like. The gap between base and total comp is where real money hides.
On negotiation: Leverage military transition benefits. Hampton Roads employers value candidates with security clearances and military technical experience. The range for Federated Learning Engineers in Virginia Beach runs from $136,000 to $241,000. That is not a narrow window. Where you land inside it depends almost entirely on whether you negotiate and how well you prepare.
Sources: SEC filings, H-1B LCA (DOL), BLS OES, 50+ job posting platforms. COL: BEA Regional Price Parities (2025). Data verified by Justin Bartak, Founder & Chief AI Officer. Last verified April 8, 2026. Full methodology
Considering a related role?
- A LLM Engineer in Virginia Beach earns $181,000 (1% less)
- The highest-paying role in Virginia Beach is Distinguished Engineer at $336,000
Common questions.
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