Machine Learning Engineer vs Financial Advisor Salary
Machine Learning Engineers earn approximately 43.0% more than Financial Advisors nationally — $165,000 vs $94,000.
Machine Learning Engineer vs Financial Advisor: salary breakdown
On a national-median basis, Machine Learning Engineers out-earn Financial Advisors by $71,000 per year — a 43.0% gap. That works out to roughly $5,917/month or $34/hour of difference.
Important context: these are MEDIANS — the middle salary in the country. Real-world variation is wide: entry-level roles in either career may pay 25-35% below median, while senior roles or specialized niches can pay 50-100%+ above. Your specific numbers depend on experience, location, employer, and credentials.
When does the salary gap matter most?
For someone choosing between these careers, the $71,000 annual difference compounds:
- Over 10 years: ~$710,000 in raw salary difference
- Over 40 years: ~$2,840,000 (without raises or compounding)
- With 3% annual raises: the gap typically grows because the higher-paid role's raises are also larger in dollar terms
- With investment compounding: the $71,000/year extra invested at 7% over 40 years grows to roughly $14,129,000 — significantly more than the raw difference
But salary isn't everything. Job satisfaction, work-life balance, growth potential, and career switching costs all matter. A career you can sustain for decades beats a higher-paying one you'll burn out on.
By state and city — significant variation
National medians are starting points. Real salaries vary 30%+ by location:
- Machine Learning Engineer in California ≈ $194,700 (1.18× national)
- Machine Learning Engineer in Mississippi ≈ $138,600 (0.84× national)
- Financial Advisor in California ≈ $110,920
- Financial Advisor in Mississippi ≈ $78,960
Use our Machine Learning Engineer salary by state pages to drill into specific locations.
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