Envié una solicitud electrónica. El proceso duró 1 día. Acudí a una entrevista en Amazon (San Jose, CA) en ene 2016
Entrevista
They sent me a coding challenge. The first half was easy. It was about finding bugs in small programs. The second half required you to do multiple questions about logics and puzzles. I screwed that up. 40 questions in 40 minutes. The last one was a coding question. Easy in nature. But I had to find an optimized algorithm for it and it took quite a long time. They gave me 30 mins.
The recruiter was kind, he extended the coding challenge for me twice, though 2 times I had problem logging in the system to do the coding challenge. So I had to contacted the system's support team and they resolved it very quickly within a day.
Preguntas de entrevista [1]
Pregunta 1
Count distinct pair of integers that sum up to a target number.
Interviewed for silicon team. Have only been asked about the domain specific knowledge in 1st round and system design in 2nd round and C coding in 3rd round.
The interviews were 50 mins each.
First round with hr screening - 2 leetcode questions then hr manager screening then the loop which consists of 4 interviews each an hour long. The 4 interview questions they asked where three medium leetcode questions. And one system design interview question about how to shadow deploy a test software to millions of users.
The phone screen went longer than expected, focusing heavily on implementation details. The interviewer really grilled me on my approach to a Least Recently Used (LRU) cache, asking how I'd combine a hashmap with a doubly linked list. I felt well-prepared since I had gone through system design examples on PracHub, which made me comfortable discussing eviction policies. The later rounds included more technical questions and behavioral interviews, but in the end, I received an offer, though I ultimately decided to decline. Overall, I’d say the process was average, with solid questions.
Preguntas de entrevista [1]
Pregunta 1
Design and implement a Least Recently Used (LRU) cache supporting get(key) and put(key, value) in O(1) average time. Walk through combining a hashmap with a doubly linked list, eviction policy when capacity is exceeded, and how you'd extend it to handle thread-safe concurrent access.