Expedia ML Scientist III — HM + NLP/LLM + ML coding; offer
Background:
3+ YOE as Data Scientist/MLE
B.Tech from IIT (non-circuital branch)
Interview Process
Hiring Manager Round (Eliminative)
Discussion around past projects, Python coding, and questions on NLP & LLMs. Transformer arhcitecture explanation
Full Loop (3 Rounds)
Round 1 — NLP + LLMs (Deep Dive)
Word embeddings, why word embeddings?, transformers architecture, topic modeling (since I have worked on it), aspect extraction, etc
Round 2 — Coding (ML + DSA)
One question involved computing text similarity. And, one graph based question - medium level
Round 3 — ML Fundamentals + Applied ML + NLP
Covered bias-variance tradeoff, probability, regularization, RNNs, attention mechanisms, seq2seq , etc
Compensation details : https://leetcode.com/discuss/post/7277000/expedia-ml-scientist-iii-offer-breakdown-iivf/
The loop · 4 rounds
Eliminative: past projects, Python coding, NLP/LLM, transformer architecture explanation
NLP + LLMs deep dive: word embeddings, transformers, topic modeling, aspect extraction
Coding (ML + DSA): text similarity computation, medium graph problem
ML Fundamentals: bias-variance, probability, regularization, RNNs, attention, seq2seq