I applied online. The process took 1 week. I interviewed at Amazon
Interview
Interviewed for a machine learning internship in Seattle. Process took one week. I got an email from a recruiting coordinator to fix a time for a technical interview. I had a first phone interview after 4 days. Questions were about my research and technical ones were asked in the context of a technical problem where I was asked to improve a recommender system given a specific training dataset. I received a second email from the recruiter for a second technical interview which was similar to the first one. Both interviews were fairly easy and interviewers were very nice.
Interview questions [1]
Question 1
Questions were about designing / improving recommender systems given a specific training data set.
I applied online. The process took 5 weeks. I interviewed at Amazon in Mar 2016
Interview
Applied on line. Took five weeks before the HR first contacted. The HR replied email timely since then.
It was sort of weird as I didn't apply to a speech team, yet the HR mentioned the speech team would want to interview. Lacking first hand speech background. I used nlp courses from Stanford (the one on coursera and the one on deep leaning) and automatic speech recognition course offered by U. Edinburgh to gain some knowledge. Previous interview questions at glassdoor helped a lot in pointing
to the directions.
The interview was moved ahead for an hour the day before the scheduled interview. The interviewer was also late for 10 minutes.
The interviewer start by asking what kind of machine learning techniques I have used in either my academic or internship career. I tried to link my experience to GMM, HMM, dimensional reduction, which shows up in automatic speech recognition. He then sort of based on what I said to ask questions. The questions were:
1. How does GMM/HMM work
2. Name some dimensional reduction method; I said PCA and we talked a bit about how PCA works and what's the physical intuiation
3. How K-means work, what kind of distance metric would you choose, what if different features have different dynamic range
4. How GMM works (EM algorithm)
In the near future I suspect people would need knowledge in DNN/HMM.
We then moved on to online coding, the HR had sent a link beforehand.
I was asked to either code in C or Java. I screwed up, both in algorithm and in coding.
The question was, given a function with inputs --an array with N randomly sorted numbers, and an int K, return output in an array with the K largest numbers.
Overall it was a positive interview experience as the interviewer was nice in general.
Interview questions [1]
Question 1
Q: Given a function with inputs --an array with N randomly sorted numbers, and an int K, return output in an array with the K largest numbers.
Q:
1. How does GMM/HMM work
2. Name some dimensional reduction method; I said PCA and we talked a bit about how PCA works and what's the physical intuiation
3. How K-means work, what kind of distance metric would you choose, what if different features have different dynamic range
4. How GMM works (EM algorithm)
I applied online. The process took 2 weeks. I interviewed at Amazon in Mar 2016
Interview
I have only taken a technical phone interview till now. The interview last about 1 hour. I have talked with one of the engineers in Amazon's speech group. My interviewer has Indian accent. And through a phone call, quite difficult for me to understand him. He spent too much time asking me about machine learning questions and left little time for the programming part.
Interview questions [1]
Question 1
How can you find a unique list of customers who visited on day 1 and then came back for a visit on day 2?