Senior ML Ops Engineer - Nas Neuron
Hospitals and Health Care Company United Arab Emirates
Sharjah, United Arab Emirates
Machine Learning Engineers in Sharjah, United Arab Emirates earn a median annual salary of $90,180 per year, which translates to approximately $7,515 per month. This median figure represents the middle point of all Machine Learning Engineers salaries in Sharjah, United Arab Emirates, meaning 50% of professionals earn more than this amount, while 50% earn less.
Salaries for Machine Learning Engineers can vary widely depending on experience level. For example, an entry-level professional typically earns between $77,743 and $97,420 per year (6,478–8,118 per month). These ranges (from the 25th to 75th percentile) reflect typical earnings for each experience level, helping job seekers and employers understand what to expect in the current market.
The salary distribution for Machine Learning Engineers in Sharjah also shows significant variation based on skills, company size, and industry. At the 25th percentile, Machine Learning Engineers earn $69,178 annually ($5,764 monthly), representing salaries at the lower end of the spectrum. The 75th percentile reaches $98,060 per year ($8,171 monthly), typically achieved by the most experienced Machine Learning Engineers with specialized skills.
Top-tier Machine Learning Engineers in Sharjah, representing the 90th percentile, command salaries of $100,220 annually ($8,351 monthly) or higher.
The United Arab Emirates's tax-free income policy makes these salaries particularly attractive compared to other global tech hubs. A $95,000 salary in Sharjah provides the same take-home pay as approximately $127,000 in London or $135,000 in New York after accounting for income taxes. This tax advantage, combined with Sharjah's strategic location and growing tech ecosystem, continues to attract Machine Learning Engineer talent from around the world.
These salary ranges are based on 173 data points and salary submissions. Data includes base salaries from companies of all sizes across various industries. Learn more about our methodology →
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