2 min readfrom Machine Learning

[D] Diffusion research interview experience?

Sorry in advance, these might be bad questions, as I don't have any interviews right now and thus no specific questions, but I'm trying to get a realistic picture of what technical questions come up when interviewing for Research Scientist or Research Engineer roles focused on diffusion, so I can prepare better in the future.

Here are some things I'm wondering about, but feel free to include other stuff not listed here, also don't have to answer all questions:

  • How did you prepare? Any specific papers, books, courses etc?
  • What kind of questions did they ask? Did you also need to prepare for system design and leetcode questions?
  • What specific diffusion-related topics came up most often?
  • For RS: Were there proof-heavy questions, derivations from scratch or discussions of open theoretical problems?
  • For RE: How much emphasis was there on implementation details, scaling, evaluation, or real-world adaptations (to like different modalities I guess or real use cases)?
  • Did they ask you to critique recent papers, propose extensions to existing diffusion work, or brainstorm new research directions on the spot?
  • Any surprising or unusually hard technical questions you remember?

Thanks in advance!

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