AI and ML Salaries Explained

A salary number is only meaningful when its source, occupation, geography, date, and pay definition are clear. The U.S. Bureau of Labor Statistics’ Occupational Employment and Wage Statistics program publishes wage distributions by occupation and geography, not an “AI engineer” salary table. For context, its May 2025 U.S. data put the data-scientist 10th-to-90th-percentile wage range below $67,240 to above $199,130, with a $120,230 median; computer and information research scientists below $82,200 to above $230,630, with a $140,300 median; and software developers below $82,460 to above $214,670, with a $135,980 median. These are broad occupation proxies, not a range that every AI job should pay. BLS describes these as wage and salary estimates for U.S. employees; they do not include nonproduction bonuses, stock bonuses, or employer costs for benefits. The wage distribution is not a promised entry-to-senior pay ladder. As one employer-specific example, when accessed September 27, 2026, Amazon’s active Senior Machine Learning Engineer, AWS Applied AI Solutions posting listed a base salary range of $168,100–$227,400 for Seattle, Washington and separately described sign-on payments and restricted stock units. The posting says final compensation depends on factors such as experience, qualifications, and location. That one range is not a survey result, an offer guarantee, or a benchmark for all ML engineers. For comparisons, separate base pay from bonus, equity, benefits, and location adjustments. Check whether the range is annual base, hourly pay, total compensation, or a survey estimate. Compare similar levels and work scopes, note the data year, and use local and industry tables when available. A recruiter’s or employer’s current information is more relevant to a specific offer than an older national median, while public survey data can show a broad distribution without predicting an individual outcome.