AI/ML Research Scientist to ML/AI Engineer

Summary: 2 of the 6 core skills listed for ML/AI Engineer carry over directly from AI/ML Research Scientist, and 3 more build on related experience. The US median salary changes by -8% ($180K → $165K). Difficulty: Moderate, typically around 6 months of focused upskilling.

The two roles

AI/ML Research Scientist: Conduct research to advance artificial intelligence and machine learning.

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
• Deep Learning

Builds on related experience

• Machine Learning — builds on Deep Learning
• TensorFlow — builds on Deep Learning
• MLOps — builds on Deep Learning

Skills to learn for ML/AI Engineer

• Cloud

Salary comparison (median, estimated)

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

Next steps

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Related

AI/ML Research Scientist career guide | ML/AI Engineer career guide

Other transitions to consider

• AI/ML Research Scientist to Data Scientist — 2 of the core skills carry over
• AI/ML Research Scientist to Quantitative Analyst (Quant) — 4 of the core skills carry over
• AI/ML Research Scientist to Computer Vision Engineer — 6 of the core skills carry over
• AI/ML Research Scientist to Research Scientist — 2 of the core skills carry over
• Data 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
• Data Engineer to ML/AI Engineer — 2 of the core skills carry over