Software Engineer Machine Learning
$116,209 (USD)/yr
$55.87 (USD)/hr
$5,334 (USD)/yr
The average software engineer machine learning gross salary in Guam, United States is $116,209 or an equivalent hourly rate of $56. This is 15% lower (-$19,738) than the average software engineer machine learning salary in the United States. In addition, they earn an average bonus of $5,334. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Guam, United States. An entry level software engineer machine learning (1-3 years of experience) earns an average salary of $81,337. On the other end, a senior level software engineer machine learning (8+ years of experience) earns an average salary of $132,340.
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$132,124 (USD)
14 %
Based on our compensation data, the estimated salary potential for Software Engineer Machine Learning will increase 14 % over 5 years.
This chart displays the highest level of education for:
Software Engineer Machine Learning, the majority at 100% with bachelors.
Typical Field of Study: Computer Programming, Specific Applications
See how education can impact your salaryThe cost of living in Guam, United States is 24% more than the average cost of living in the United States. Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.
View Cost of Living PageGuam ( GWAHM; Chamorro: Guåhan [ˈɡʷɑhɑn]) is an island that is an organized, unincorporated territory of the United States in the Micronesia subregion of the western Pacific Ocean. Guam's capital is Hagåtña, and the most populous village is Dededo. It is the westernmost point and territory of the United States, as measured from the geographic center of the U.S. with point Udall. In Oceania, Guam is the largest and southernmost of the Mariana Islands and the largest island in Micronesia. In 2022
Sourced from WikipediaERI's compensation data are based on salary surveys conducted and researched by ERI. Cost of labor data in the Assessor Series are based on actual housing sales data from commercially available sources, plus rental rates, gasoline prices, consumables, medical care premium costs, property taxes, effective income tax rates, etc.
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