Machine Learning Engineer vs Operations Manager Salary

Machine Learning Engineers earn more nationally. The median annual salary for Machine Learning Engineers is $158,000 versus $107,580 for Operations Managers — a difference of $50,420 per year or $4,202 per month.

The national median salary gap between Machine Learning Engineers and Operations Managers is $50,420 per year. Machine Learning Engineers earn 32% more. Over a 30-year career this difference, if invested at 7% annual return, compounds to approximately $571,526.

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 Operations Managers the highest median salary at $138,580 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 General and Operations 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 Operations Managers earn approximately $52 per hour. Actual hourly rates vary based on overtime, part-time work, and whether the role is salaried or hourly.