CS-OA cs-vo Faang

Anthropic SDE – 一亩三分地面经 – 面试代面 – 代面试 – 面试辅助 – interview proxy

product SDE 岗位,流程如下:

OA: 地里的面经,前3个part满分,最后一个好像是80%的case过了


Your task is to implement a simplified version of an in-memory database. Plan your design according

to the level specifications below:

Level 1: In-memory database should support basic operations to manipulate records,

fields, and values within fields.

Level 2: In-memory database should support displaying a specific record's fields based on a


Level 3: In-memory database should support TTL (Time-To-Live) configurations on database


Level 4: In-memory database should support backup and restore functionality.

To move to the next level, you need to pass all the tests at this level.


You will receive a list of queries to the system, and the final output should be an array of strings

representing the returned values of all queries. Each query will only call one operation

电面:有一个已经写好了的beautiful soup python web crawler function, given url and returns all urls on this url,然后让写一个web crawler,given root domain,抓取这个domain下所有的url,这个部分需要写代码,并且work。基本上就是一个bfs,然后记录已经抓过的url避免重复即可。第二个部分问如果要提升crawler效率怎么做,用的asyncio来实现异步处理,可以提前看一下怎么用。同时会问一些system design的问题,比如如何scale,如果expand到更多root domain

VO1: coding + system design,假设你有一个uber api,given longitude and latitude, return true iff the coordinate is in surge area。然后让写一个function,given a longitude and latitude, return path or coordinate so that the user can walk to the location outside of the surge area。这轮的代码不用run。这里lz想复杂了,说用bfs,但是实际上只要找上下左右四个方向最近的path就可以。然后接着问了一些system design问题,比如如何scale,如何防止我们的function crash uber api, etc

VO2: HM BQ,很标准的BQ,没啥好说的

VO3: culture round,也是一轮BQ,但是会问一些比较灵性的问题比如怎么看待AI的risk,对AI最大的concern是什么。LZ直接看的recruiter发的anthropic官方博客里的文章,里面会提到这些内容

VO4:system design,题目是让design一个prompt playground,类似于chatgpt playground,让你从product的角度说需要哪些require‍‌‌‌‍‍‌‌‌‍‌‌‌‍‍‌‌‌‍‌‌ment,怎么实现,怎么scale。面试的形式跟其他大厂的system design不太一样,问题很偏product/full-stack,面试官会walk through everything with you and take note for you,然后让我只要一直讲下去就行
一天后邮件通知not move forward



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