JPMC MLCoE NLP Scientist – interview experience? (4 rounds total)[N]

Hey everyone, I have my first round coming up next week for the NLP Scientist role at JP Morgan's Machine Learning Center of Excellence (MLCoE). There are 3 more rounds after that, and I'm trying to get a sense of what to expect at each stage.

If you've interviewed for this team (or a similar MLCoE / Applied AI role at JPMC) recently, I'd really appreciate any insight on:

Round structure - which rounds focus on coding vs. ML theory vs. system design vs. behavioral?

NLP depth - how far do they go into transformers, RAG, fine-tuning, evaluation methods, and recent LLM topics?

Research presentation - is there one? How is it structured?

Coding - LeetCode-style, ML-flavored, or applied (e.g., "build a quick pipeline")?

Domain knowledge - how much finance/regulatory context do they expect upfront?

Behavioral - I've read JPMC weighs Business Principles heavily. True for MLCoE too?

Timeline - rough gap between rounds and to a decision?

Any prep resources, traps to avoid, or "I wish I'd known this" stories would be incredibly helpful. Happy to pay it forward with a write-up after my loop wraps up.

Thanks!