ML/AI Engineer to Data Engineer

Summary: 1 of the 6 core skills listed for Data Engineer carry over directly from ML/AI Engineer, and 1 more build on related experience. The US median salary changes by -21% ($165K → $130K). Difficulty: Challenging, typically around 9 months of focused upskilling.

The two roles

ML/AI Engineer: Build and deploy machine learning models into production systems.

Data Engineer: Build and maintain data pipelines and infrastructure for analytics. Growth outlook +30%; AI-augmented (AI changes how the work is done, not whether it exists). Typical education: bachelor. Typical experience: 2+ years.

Skills that carry over

• Python

Builds on related experience

• Cloud Platforms — builds on Cloud

Skills to learn for Data Engineer

• SQL
• ETL
• Data Warehousing
• Spark

Salary comparison (median, estimated)

Salary figures are estimates benchmarked against public compensation data — see methodology.

Next steps

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Related

ML/AI Engineer career guide | Data Engineer career guide

Other transitions to consider

• ML/AI Engineer to Data Scientist — 2 of the core skills carry over
• ML/AI Engineer to AI/ML Research Scientist — 3 of the core skills carry over
• ML/AI Engineer to Backend Developer — 5 of the core skills carry over
• ML/AI Engineer to Quantitative Analyst (Quant) — 4 of the core skills carry over
• Data Scientist to Data Engineer — 5 of the core skills carry over
• Data Analyst to Data Engineer — 5 of the core skills carry over
• Database Administrator to Data Engineer — 5 of the core skills carry over
• Backend Developer to Data Engineer — 6 of the core skills carry over