After initial contact with the recruiter, I skipped the technical screen and proceeded to the first round of interviews. This round consisted of one hour of coding and one hour of machine learning concepts. I would describe it as an honest but hard interview. Anything you claim you've done on your resume, you must be able to speak to in great detail. The interviewers were very nice and both were incredibly smart.
Coding:
Two LeetCode questions. The first was easy-ish, but an optimal solution was needed. The second was easy, maybe medium, and also required an optimal solution. Time and space complexity were definitely discussed.
ML Concepts:
The interviewer was incredibly knowledgeable and thorough, asking very detailed technical questions about all the models on my resume. They probed about choices made and subtle differences between models. Concepts like gradient boosting were explained, as well as the difference between XGBoost and LightGBM.
The following metrics were computed from 1 interview experience for the Instacart Machine Learning Engineer role in New York, New York.
Instacart's interview process for their Machine Learning Engineer roles in New York, New York is extremely selective, failing the vast majority of engineers.
Candidates reported having very good feelings for Instacart's Machine Learning Engineer interview process in New York, New York.