Data Engineer to ML/AI Engineer

Summary: 1 of the 6 core skills listed for ML/AI Engineer carry over directly from Data Engineer, and 1 more build on related experience. The US median salary changes by +27% ($130K → $165K). Difficulty: Challenging, typically around 9 months of focused upskilling.

The two roles

Data Engineer: Build and maintain data pipelines and infrastructure for analytics.

ML/AI Engineer: Build and deploy machine learning models into production systems. Growth outlook +40%; AI-resistant. Typical education: master. Typical experience: 3+ years.

Skills that carry over

• Python

Builds on related experience

• Cloud — builds on Cloud Platforms

Skills to learn for ML/AI Engineer

• Machine Learning
• TensorFlow
• MLOps
• Deep Learning

Salary comparison (median, estimated)

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

Next steps

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Related

Data Engineer career guide | ML/AI Engineer career guide

Other transitions to consider

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