ML Engineer vs. Research Scientist: Understanding the Difference

Confused about whether to pursue an ML Engineering or Research Scientist role? Here's the breakdown. ## ML Engineer - Focus: Production systems, scalability, deployment - Skills: Software engineering, MLOps, system design - Output: Working models in production - Education: BS/MS in CS or related field ## Research Scientist - Focus: Novel algorithms, academic publications - Skills: Advanced mathematics, experimentation, paper writing - Output: Research papers, prototypes - Education: PhD preferred (but not always required) ## Which Path is Right for You? If you love building robust systems → ML Engineer If you love solving unsolved problems → Research Scientist