Research Scientist → ML Engineer (Industry)
Translate research excellence into production systems
Research scientists excel at novel approaches but often lack production discipline. This path teaches software engineering practices, testing, DevOps, and how to ship ML at scale.
TARGET ROLE
ML Engineer, Senior ML Engineer
SALARY RANGE
$150,000–$220,000
DIFFICULTY
Intermediate
WHAT'S INCLUDED
Tracks in This Path
This path combines 2 curated learning tracks, sequenced to build on each other.
LEARNING OUTCOMES
What You'll Be Able To Do
By the end of this path, you'll have concrete, job-ready skills.
Master software engineering best practices: Git, testing, code review
Learn MLOps and model deployment pipelines
Understand production constraints: latency, cost, reliability
Implement monitoring and drift detection
Write production-quality code from day one
Ship an industry ML project
FAQ
Common Questions
Why do research scientists struggle in industry?+
Will I lose my research edge?+
How different are research and industry ML?+
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Last updated: 2026-03-07