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ML Engineer vs Data Scientist Salary Comparison

ML engineer vs data scientist salary comparison tool: ESTIMATED compensation benchmarks across industries, experience levels, and locations using Glassdoor and Payscale data.

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Showing — rows ★ Estimates only — see methodology below
Job Title ⇅Industry ⇅Experience Level ⇅Base Salary ESTIMATE (USD) ⇅Total Compensation ESTIMATE (USD) ⇅Bonus ESTIMATE (USD) ⇅Stock ESTIMATE (USD/year) ⇅Location ⇅

Understanding the salary differences between Machine Learning (ML) Engineers and Data Scientists is crucial for professionals navigating careers in AI and data science. This ML engineer vs data scientist salary comparison tool provides ESTIMATED compensation benchmarks across industries, experience levels, and geographic locations, helping you make informed career decisions.

ML Engineers typically command higher salaries than Data Scientists, reflecting the specialized engineering skills required to productionize models at scale. According to data from Levels.fyi, Glassdoor, and Payscale, ML Engineers at top tech companies can earn total compensation packages 10-30% higher than their Data Scientist counterparts, particularly at senior levels. This gap widens in industries like finance and technology, where ML deployment is more mature.

For example, an entry-level ML Engineer in San Francisco might earn a base salary ESTIMATE of $110,000, while a mid-level Data Scientist in the same city could expect around $130,000. However, these figures vary significantly by location—professionals in New York or Boston may see slightly lower salaries, though cost-of-living adjustments often balance these differences.

The data in this tool aggregates public salary reports from sources like the Bureau of Labor Statistics, LinkedIn Talent Insights, and Levels.fyi, focusing on base salary, bonuses, and equity ESTIMATES. While precise figures depend on company size, individual negotiation, and role specifics, this comparison provides a data-driven starting point for your ML engineer vs data scientist salary research.

How It Works

This comparison tool lets you filter salary ESTIMATES by job title, industry, experience level, and location. Each row represents aggregated compensation data from public sources, adjusted for regional and industry variations.

  • Base Salary: Median annual salary ESTIMATE, excluding bonuses or equity.
  • Total Compensation: Base salary + ESTIMATED annual bonuses + stock grants (where applicable).
  • Bonus: ESTIMATED annual bonus as a percentage of base salary.

Use this data to benchmark your current compensation or evaluate job offers in the AI/ML field.

Methodology Note

All salary figures are ESTIMATES based on aggregated data from Glassdoor, Payscale, Levels.fyi, and the Bureau of Labor Statistics. Compensation varies by company, negotiation, and economic conditions. This tool does not represent guaranteed salaries but provides a data-driven range for ML engineer vs data scientist salary comparisons.

Frequently Asked Questions

Why do ML Engineers typically earn more than Data Scientists?
ML Engineers focus on deploying and scaling models in production environments, requiring software engineering skills (e.g., API development, MLOps, infrastructure) that are in high demand. Data Scientists often concentrate on analytical modeling, experimentation, and insights, which may have narrower salary ranges. This skill premium is reflected in salary ESTIMATES, especially at senior levels.
How accurate are these salary ESTIMATES?
The figures aggregate public salary data from reputable sources like Glassdoor, Payscale, and Levels.fyi. While they represent realistic ranges, actual compensation depends on company size, location, negotiation, and market conditions. Treat these as ESTIMATED benchmarks rather than exact figures.
Do ML Engineer salaries vary significantly by industry?
Yes. Technology and finance industries tend to offer the highest compensation for ML Engineers, with total ESTIMATED packages often exceeding $200,000 for senior roles. Healthcare and retail sectors may offer lower base salaries but may include other benefits like flexible work arrangements.
Are bonuses and stock included in these salary ESTIMATES?
Total compensation includes ESTIMATED annual bonuses and stock grants (where applicable), particularly for mid-level and senior roles. Entry-level positions may have minimal or no equity components.
How does location impact ML Engineer vs Data Scientist salaries?
Salaries in tech hubs like San Francisco, New York, or Seattle are typically 10-20% higher than national averages to account for cost of living. However, remote roles or companies in lower-cost regions may offer competitive salaries without geographic premiums.
What skills can increase my salary as a Data Scientist or ML Engineer?
For Data Scientists: Advanced statistical modeling, domain expertise (e.g., healthcare, finance), and big data tools (Spark, Hadoop) can boost earning potential. For ML Engineers: MLOps, cloud infrastructure (AWS/GCP), and production-scale deployment skills command higher salaries.
Are there gender pay gaps in ML Engineer vs Data Scientist salaries?
Studies from LinkedIn and the Bureau of Labor Statistics suggest persistent gender pay gaps in tech, though the gap narrows for roles requiring specialized engineering skills. ML Engineers, due to higher demand for infrastructure expertise, may see smaller disparities than Data Scientists.
How often should I expect salary adjustments in these roles?
Tech industry norms vary, but many companies conduct annual performance reviews with potential salary adjustments. ML Engineers at high-growth startups may see more frequent adjustments due to skill shortages, while Data Scientists in established firms may experience slower raises.
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