Machine Learning Engineers in Riyadh, Saudi Arabia earn a median annual salary of $85,935 per year, which translates to approximately $7,161 per month. This median figure represents the middle point of all Machine Learning Engineers salaries in Riyadh, Saudi Arabia, 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 $17,465 and $48,599 per year (1,455–4,049 per month), while a junior Machine Learning Engineer can expect a range of $39,500 to $77,975 annually (3,291–6,497 per month), intermediate professionals often see salaries from $49,738 to $83,323 per year (4,144–6,943 per month), and senior-level roles can command between $80,960 and $105,945 annually (6,746–8,828 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 Riyadh also shows significant variation based on skills, company size, and industry. At the 25th percentile, Machine Learning Engineers earn $50,438 annually ($4,203 monthly), representing salaries at the lower end of the spectrum. The 75th percentile reaches $103,478 per year ($8,623 monthly), typically achieved by the most experienced Machine Learning Engineers with specialized skills.
Top-tier Machine Learning Engineers in Riyadh, representing the 90th percentile, command salaries of $116,418 annually ($9,701 monthly) or higher.
The Saudi Arabia's tax-free income policy makes these salaries particularly attractive compared to other global tech hubs. A $95,000 salary in Riyadh 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 Riyadh's strategic location and growing tech ecosystem, continues to attract Machine Learning Engineer talent from around the world.
