U.S. Immigration Data

Priority dates, work visas, and labor market data

Software Engineer, Machine Learning

H-1B & Green Card Salary Data and Market Analysis

234

Total Filings

All time (charts below use selected years)

$164,800

Median Salary

Across filings in selected period

+43.8%

Filing Growth

16 → 23 filings, FY2021 to FY2026

15

Top Employers

Hiring This Role
Salary Distribution (All Employers + Top Employer Overlays)
10th Percentile

$135,283

25th Percentile

$154,000

Median (50th)

$164,800

75th Percentile

$175,100

90th Percentile

$210,623

See all H-1B/PERM filings for this role →

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Top Employers Hiring Software Engineer, Machine Learning
Employer Filings Median Salary Salary Range Approval Rate
LinkedIn Corporation 114 $162,091 $130,894 - $184,662 86.0%
META PLATFORMS, INC. 26 $211,399 $147,368 - $275,465 88.5%
DoorDash, Inc. 5 $213,998 $200,000 - $215,197 80.0%
BYTEDANCE INC. 2 $167,790 $167,790 - $167,790 100.0%
Match Group LLC 2 $182,500 $175,000 - $190,000 100.0%
Roku, Inc. 2 $270,000 $270,000 - $270,000 50.0%
SNAP INC. 2 $205,250 $190,000 - $220,500 100.0%
Microsoft Corporation 2 $185,205 $162,510 - $207,900 100.0%
NEEVA INC. 2 $178,820 $172,640 - $185,000 100.0%
Facebook, Inc. 2 $180,000 $165,000 - $195,000 100.0%
7-Eleven, Inc. 2 $128,987 $125,000 - $132,974 100.0%
Cortical.io USA Inc. 2 $110,918 $110,918 - $110,918 100.0%
Kumo.ai, Inc. 2 $185,000 $185,000 - $185,000 50.0%
FOURSQUARE LABS, INC. 1 $160,000 $160,000 - $160,000 100.0%
Grata Inc 1 $123,614 $123,614 - $123,614 100.0%
Geographic Distribution
Based on 193 filings in selected period (charts use selected years, not all-time total)
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Median Salary by State
Based on selected period (same 193 filings as above)
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Top Metro Areas
City State Filings Median Salary
Sunnyvale CA 88 $161,801
New York NY 14 $164,100
San Francisco CA 9 $190,000
Menlo Park CA 8 $208,617
Mountain View CA 7 $165,000
Seattle WA 4 $198,381
Bellevue WA 3 $167,790
Redmond WA 2 $185,205
Pittsburgh PA 2 $82,774
Irving TX 1 $125,000

What different H-1B workers are actually paid

Across the 244,862 petitions we hold for the H-1B cap lottery as a whole, the I-129 filing records the beneficiary's actual pay alongside their country of birth, education and gender. A raw pay gap between two groups is mostly a statement about which jobs they hold — so each gap below is shown twice: as it looks raw, and again measured within the same job title. The second number is the one to read.

Gender is here as the control. Our decomposition of the H-1B gender pay gap found that gap is sorting almost entirely — it survives the correction at under a percent. Country of birth and education do not behave that way: part of each gap is job mix, and a real difference is still standing after the correction.

Country of birth

Group Petitions Median actual pay Raw gap vs everyone Within the same job title Explained by job mix
India 164,659 $90,397 -$2,288 -$2,411
China 35,095 $110,000 +$17,315 +$8,896 48.6%
Philippines 1,863 $64,000 -$28,685 -$594 97.9%

60 other values (39,441 petitions) are not shown, because too few of their petitions sit in a job title big enough to compare within. Only a raw figure exists there — and a raw figure is the thing this table corrects, so ranking it beside these would mislead rather than inform.

Education level

Group Petitions Median actual pay Raw gap vs everyone Within the same job title Explained by job mix
Master's degree 102,816 $91,104 -$896 -$262
Bachelor's degree 88,784 $90,000 -$2,000 -$1,219 39.0%
Doctorate degree 11,783 $128,400 +$36,400 +$17,739 51.3%
Professional degree 2,272 $150,000 +$58,000 +$24,154 58.4%

One other value (103 petitions) is not shown, because too few of its petitions sit in a job title big enough to compare within. Only a raw figure exists there — and a raw figure is the thing this table corrects, so ranking it beside these would mislead rather than inform.

Gender

Group Petitions Median actual pay Raw gap vs everyone Within the same job title Explained by job mix
Men 164,128 $93,891 +$1,206 -$361
Women 80,734 $90,000 -$2,685 +$469

How to read this. The within-occupation figure compares people holding the same job title, weighted by how many petitions sit in each title. Titles encode seniority, so equal pay within a title does not rule out differences in reaching that title — the same limitation that applies to any controlled pay-gap number. Figures are base pay only: the I-129 reports prospective base compensation, with no equity or bonus, so this is not total compensation. Coverage is FY2021–FY2024 cap-subject H-1B lottery petitions that carry both a pay figure and a job title — a one-time FOIA snapshot, not a live feed. Aggregates only, with small counts suppressed. Source: I-129 petition data sourced from USCIS, obtained by Bloomberg.

Related Roles & Career Progression

These roles are variations of Software Engineer, Machine Learning with different seniority levels.

Role Experience Level Filings Avg Salary
Software Engineer, Machine Learning Unspecified 232 $166,054
Software Engineer - Machine Learning and Motion Planning Unspecified 1 $80,933
Software Engineer, Machine Learning and Search Ranking Unspecified 1 $185,000
Filing Volume Trend
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Median Salary Trend
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Year-over-Year Statistics
Fiscal Year Filings Median Salary Approval Rate
2021 16 $153,960 93.8%
2022 48 $162,460 93.8%
2023 36 $165,483 91.7%
2024 45 $167,149 88.9%
2025 25 $170,186 68.0%
2026 23 $170,186 82.6%
Company Comparison - Software Engineer, Machine Learning

Compare how top companies pay for this role.

Company Filings Median Salary Approval Rate
LinkedIn Corporation 114 $162,091 86.0%
META PLATFORMS, INC. 26 $211,399 88.5%
DoorDash, Inc. 5 $213,998 80.0%
BYTEDANCE INC. 2 $167,790 100.0%
Match Group LLC 2 $182,500 100.0%
Data Source: U.S. Department of Labor (DOL) H-1B and green card (PERM) disclosure data. Data shown for fiscal years 2021 to present. Last updated: August 31, 2026

Note on Salary Data: For data quality, we exclude salaries below $30,000 (likely data entry errors) and above $1,000,000 (lacking automated validation for ultra-high compensation packages). This may affect statistics for some executive and specialized positions.