Machine Learning Engineer vs Data Scientist Salary 2026

Machine Learning Engineer vs Data Scientist Salary: Quick Comparison

The national average salary for a Machine Learning Engineer is $168,000/year, while a Data Scientist earns an average of $148,000/year. Machine Learning Engineers earn $20,000 more on average (13% higher than Data Scientists). Here’s a full breakdown to help you decide which path is right for you.

Metric	Machine Learning Engineer	Data Scientist
National Average (2026)	$168,000	$148,000
Monthly (avg)	$14,000	$12,333
Hourly (avg)	$80.77	$71.15
Entry-Level	$105,840	$93,240
Mid-Level	$137,760	$121,360
Senior	$198,240	$174,640
Director / Principal	$238,560	$210,160
5-yr Job Growth	40% (exceptional growth)	35% (much faster than average)
Education Required	Master’s or PhD; deep ML/DL expertise required	Master’s or PhD often preferred; strong statistics background required

Machine Learning Engineer vs Data Scientist: Salary by Experience Level

Both roles reward experience, but the trajectory differs. Here’s how salaries compare at each level:

Level	Machine Learning Engineer	Data Scientist	Difference
Entry-Level (0–2 yrs)	$105,840	$93,240	+$12,600
Mid-Level (2–5 yrs)	$137,760	$121,360	+$16,400
Senior (5+ yrs)	$198,240	$174,640	+$23,600
Director / Principal	$238,560	$210,160	+$28,400

Which Career Pays More Long-Term: Machine Learning Engineer or Data Scientist?

Both roles offer strong long-term earning potential, but Machine Learning Engineers currently earn more on average. Over a 10-year career, this compounds significantly:

Machine Learning Engineer: Cumulative 10-yr earnings estimate: ~$1,891,680
Data Scientist: Cumulative 10-yr earnings estimate: ~$1,666,480

These are rough estimates assuming steady progression. Career trajectory, specialization, and company type matter enormously — a Data Scientist at a top-tier tech company can easily out-earn a Machine Learning Engineer at a mid-market firm.

Job Growth: Machine Learning Engineer vs Data Scientist

Salary isn’t the only factor — job security and growth matter too.

Role	5-Year Job Growth (BLS)
Machine Learning Engineer	40% (exceptional growth)
Data Scientist	35% (much faster than average)

Source: Bureau of Labor Statistics Occupational Outlook Handbook

Which Should You Choose?

Choose Machine Learning Engineer if:

You’re drawn to building products and systems at scale
The 40% job growth trajectory excites you
You’re comfortable with the education path: Master’s or PhD; deep ML/DL expertise required
The $168,000 average salary meets your financial goals

Choose Data Scientist if:

You’re more interested in the core responsibilities of this role
The 35% growth rate is sufficient for your risk tolerance
You prefer the education route: Master’s or PhD often preferred; strong statistics background required
The $148,000 average aligns with your target compensation

Frequently Asked Questions

Does a Machine Learning Engineer make more than a Data Scientist?
Yes — Machine Learning Engineers earn $20,000 more on average ($168,000 vs $148,000 nationally in 2026).

Can a Data Scientist become a Machine Learning Engineer?
In many cases yes — adjacent roles like these share transferable skills. The transition typically requires upskilling in specific technical areas and may involve 6–18 months of targeted learning or a formal education program.

Which has better work-life balance: Machine Learning Engineer or Data Scientist?
Both roles vary significantly by employer and industry. Generally, work-life balance is more a function of company culture and team than job title. Ask about on-call expectations, meeting load, and team norms during interviews.

Which is harder to break into: Machine Learning Engineer or Data Scientist?
Difficulty of entry depends on your background. Both are competitive fields — Machine Learning Engineer slightly more so at top tech companies, while Data Scientist often has more paths of entry across industries.

Related Salary Guides

Salary Data Sources

Data from: Bureau of Labor Statistics, Glassdoor, LinkedIn Salary.