Machine Learning Engineer vs Human Resources Manager Salary

Machine Learning Engineers earn more nationally. The median annual salary for Machine Learning Engineers is $158,000 versus $136,350 for Human Resources Managers — a difference of $21,650 per year or $1,804 per month.

The national median salary gap between Machine Learning Engineers and Human Resources Managers is $21,650 per year. Machine Learning Engineers earn 14% more. Over a 30-year career this difference, if invested at 7% annual return, compounds to approximately $245,409.

Based on BLS OES 2024-2025 data, California pays Machine Learning Engineers the highest median salary at $212,000 per year.

Based on BLS OES 2024-2025 data, California pays Human Resources Managers the highest median salary at $172,350 per year.

Salary is one factor — Machine Learning Engineers earn more nationally. But career choice involves job satisfaction, work-life balance, education requirements, and job growth. Computer and Information Research Scientists and Human Resources Managers both have different educational paths, licensing requirements, and long-term growth projections. Use salary as a starting point, not the only factor.

Based on a standard 2,080-hour work year, Machine Learning Engineers earn approximately $76 per hour nationally and Human Resources Managers earn approximately $66 per hour. Actual hourly rates vary based on overtime, part-time work, and whether the role is salaried or hourly.