The coding question covered implementing an ML algorithm in NumPy, and the system design round is focused on a real world problem related to the team's work. Due to the fact that they are concerned about the culture, I discovered that behavioral interviews are also important to them.
- The python coding parts mainly involved working with dictionaries. - The technical parts were on hypothesis testing and experimentation. - The HR part was on standard HR questions like why yelp etc. - No feedback was provided despite having gone to the final interview which was disappointing.
do expect anything/ models on your resume
This is THE best interviewing experience I've ever had! Everyone I talked to was sharply smart but humbly polite. HR was very efficient and helpful. There are some behavior questions but all are closely to the business (e.g., how do you communicate with audiences from different backgrounds). Most rounds have cases, highly relevant to the team's business and models. For coding I personally think it is not too difficult, but they value how you approach the question/communicate/constantly think about how to improve.
Explain Vision transformers and CNN. Overfitting. Linear regression. System design involving multi-modal GenAI models.
Q. Data pre-processing coding problem Q. ML system design based on recommender system
When are you available to chat?
Obviously I cannot share the details, but what I can say is that all interviews tested an actual competency relevant to the job. This is in contrast with recent trends of "vanity interviews" where candidates are tested on things that have no relevance to the day to day work, leetcode questions for applied scientists being the best example.
What makes you the best candidate for this position?
Programming on whiteboard: Implement a regex parser.
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