If you’ve hired for research engineer / applied scientist / robotics roles:
What differentiates a strong non-PhD candidate from "Smart SWE who likes ML"?
Which artifacts are most convincing (reproducing papers, open source contributions, working on real-world systems, conference workshop paper, etc.)?
What skill gaps usually show up in interviews?
And if you’ve made the jump, what worked for you?