AI/ML Engineer vs Data Scientist

Head-to-head comparison of salary, required skills, and career outlook for two of the most in-demand AI roles.

Quick Verdict

Both roles pay similarly, so compensation shouldn't be the deciding factor. Choose AI/ML Engineer if you want more open positions (967 vs 161 currently listed). AI/ML Engineer focuses on building production ML systems, while Data Scientist centers on extracting insights and building predictive models.

Side-by-Side Comparison

Dimension	AI/ML Engineer	Data Scientist
Open Positions	967	161
Avg Salary Range	$142K–$214K	$151K–$224K
Median Salary	$212K	$222K
75th Percentile	$257K	$258K
Remote %	27%	23%
Experience Mix	Senior 92%, Mid 5%, Entry 2%	Senior 95%, Mid 5%
Top Skill	RAG	RAG

Skills Comparison

AI/ML Engineer Top Skills

RAGPythonAWSRustAzureAI AgentsPyTorchGCP

Data Scientist Top Skills

RAGPythonAWSRustPyTorchGCPAzureTensorFlow

Skills You'd Need for Both Roles

These skills appear in top-8 for both AI/ML Engineer and Data Scientist: AWS, Azure, GCP, PyTorch, Python, RAG, Rust. If you have these skills, you're well-positioned for either path.

Salary Deep Dive

AI/ML Engineer Data Scientist

25th Percentile

$158K

$184K

Median

$212K

$222K

Average

$214K

$224K

75th Percentile

$257K

$258K

Data Scientist pays 4% more on average than AI/ML Engineer.

Based on 745 and 130 job postings with disclosed compensation, respectively.

Top Hiring Companies

AI/ML Engineer

Amazon.com122 jobs

Accenture82 jobs

Amazon Web Services80 jobs

FutureSight58 jobs

Crowe LLP35 jobs

Google32 jobs

Data Scientist

Microsoft12 jobs

Amazon.com11 jobs

Information Technology Senior Management Forum10 jobs

Amazon Web Services10 jobs

GEICO5 jobs

Capital One5 jobs

Career Path

AI/ML Engineer Career Path

Typical progression: Staff ML Engineer, ML Architect, VP of Engineering. Focuses on building production ML systems.

Data Scientist Career Path

Typical progression: Senior Data Scientist, Lead Data Scientist, Head of Data Science. Focuses on extracting insights and building predictive models.

Switching Between Roles

With 7 overlapping skills (87% of top skills), transitioning between these roles is feasible with targeted upskilling.

AI/ML Engineer vs Data Scientist FAQ

Data Scientist pays more on average, with a mean salary ceiling of $224K compared to $214K for AI/ML Engineer — a 4% difference. However, top AI/ML Engineer roles at leading companies can match or exceed average Data Scientist compensation.

Yes, there is meaningful skill overlap. Both roles share these top skills: AWS, Azure, GCP, PyTorch, Python, RAG, Rust. You would need to develop expertise in Data Scientist-specific skills like domain-specific tools. Lateral moves are common in the AI industry.

AI/ML Engineer roles are 27% remote, while Data Scientist roles are 23% remote. Both offer comparable remote flexibility.

Shared top skills include: AWS, Azure, GCP, PyTorch, Python, RAG, Rust. These transferable skills make it easier to pivot between the two roles. Python and general ML knowledge are common foundations for both.

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