Interview Questions

Siddharth P. - "I believe these are the traits of a great PM. I see PM to be somone who is a great manager of customer problems and for that he/she has to be: Be an expert at the one domain and know the customer of the product in that domain and curate experiences for them better than the competition. Be persuasive - Get things done by convincing rather than commanding. Learn how great products are by being an engineer. Be a fearless leader by championing teams ideas all the way to the management la"See full answer

Imran R. - "What are some of the Tradeoff stories Amazon prefers? Do they prefer the Feature Prioritization type of tradeoff or technology/platform type of tradeoffs? "See full answer

Yash G. - " import lombok.*; import lombok.extern.slf4j.Slf4j; import org.springframework.boot.CommandLineRunner; import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.SpringBootApplication; import org.springframework.stereotype.Component; import org.springframework.stereotype.Repository; import org.springframework.stereotype.Service; import java.util.*; import java.util.concurrent.ConcurrentHashMap; import java.util.concurrent.ConcurrentMap; import java."See full answer

Pm P. - "Alexa: Is the virtual assistant that runs on amazon smart speakers as well as on other devices. Clarification on goals/Objectives: What would the goal at that point of time be? Is it increase in revenue ? Either via new customers i.e. adoption or Increasing the wallet share of the customer? Increasing the sales ordered via Alexa ? Why do people want to use Alexa? To get answers, make their lives easier by automating activities within their home Integrates with amazon account so"See full answer

M N. - "Driver retention is important to ensure growth since we need healthy retention of existing drivers while we acquire new drivers so that we meet growing demand. Should we look at a specific driver segment to improve retention? We might divide the drivers by their age on the platform: New drivers(less than 3 months since first ride), Medium age (3mos to 1 year), Long term(1+ years). Let's focus on the medium term since I assume them to be the biggest segment. Now lets try to list out possible pr"See full answer

G. D. - "It's possible the Onboarding Flow is fine as it is - but I would do some initial hands-on exploring. I would go through the boarding steps myself. Re-Visit the flow with a clean perspective. Take notes on Pros & Cons. Things I liked. Things I didn't like. Create a table. Brainstrorm some UI / UX / Flow features that could use some improvement. If my simple analysis warranted some more exploration - I would do an informal survey with my immediate internal colleagues - and possibly even my tight"See full answer

Aeshvarya J. - "Clarifying questions : When we speak about video buffering, are we looking at long video (more than an hour), medium video, short videos and shorts? I will assume its all video types. Is this was a steady increase or sudden one and over what time period? I will assume sudden one over last week? Has we experienced any such issues in the past or trends? I will assume no. Are we experiencing this globaly or for some region? I assume globaly The KPI we are measuring is Average Video Buffering T"See full answer

Surbhi G. - "While serverless computing has its merits due to removing the need for server management and auto-scaling abilities, several challenges might arise when deploying machine learning models using this setup. Cold-start latency is a key issue where an Amazon Lambda function, for example, would take more time than usual to run after being idle. This could affect the performance of real-time ML applications negatively. A way to keep the functions warm might be required to avoid this latency. Moreover,"See full answer

S G. - "Clarification questions: How are these metrics calculated? Get context on why these metrics are important? Are we looking at any specific role? Benchmarking: What is the current time to hire? How does this compare to competitors? Do we have a desired goal/target for these metrics? Problem Solving: I began by analyzing the various steps in the hiring process and the number of days taken at each stage. Soon realised that the bulk of the time is taken in a few steps (80/20). Drilled down further"See full answer

Ram - "Clarification Are we focusing on building the product on a specific Meta platform (Facebook, Instagram, WhatsApp), or is this a standalone effort? Is the product digital or physical? Are we targeting internal (employees) or external (customers) users? Are there any specific constraints like funding, resourcing, or geography? 1. Narrowing Down the Problem Awareness and Education: Create tools to increase understanding of climate change and its effects. -"See full answer

Dinar M. - "I used array to append. np.array does not have append and every np.vstack recreates object again. import numpy as np class Centroid: def init(self, location, vectors): self.location = location # (D,) self.vectors = vectors # (N_i, D) class KMeans: def init(self, n_features, k): self.nfeatures = nfeatures self.centroids = [ Centroid( location=np.random.randn(n_features), vectors=[] # I"See full answer

Unicorn 2. - "Clarifying questions: What is leisure travel? Assuming : Travel for vacation not business What is the vision/mission of the company that we are developing this for (I would like to keep this as an anchor to any users, pain points, solutions that we pick) Assuming : Brand new company - startup. Nothing specific in vision/mission for now. When we say travel user experience -> Do we have an existing product that we want to improve on? Is yes, is there any particular complaint or metric issue rel"See full answer

Beginner P. - "Skeleton: Mission Metrics to improve User segments & the segment with most impact User journey Pain points and opportunities Features/solutions & prioritization Starting with Twitter's mission, "the power to create and share ideas & information without any barriers", we are looking to empower people to be both consumers and generators of content. Are these users interacting with Twitter on the website or the mobile app? [Clarifying with interviewer, who answers mobile app.] "See full answer

Anonymous Dove - "The experience at a DMV can be improved by modernizing the systems, processes, and design of the service. Some possible ways to do this are: Using digital technologies to enable online transactions, self-service kiosks, mobile apps, and chatbots. These can reduce the need for in-person visits, shorten wait times, and increase convenience and accessibility for customers. [For example, some states have implemented online driver’s license renewal, vehicle registration, and appointment schedul"See full answer

Alick C. - "The first step is to engage the coworker. Listen to their request and try to understand the root cause of the discomfort. Is it internal or is it the environment that the team operates in, is it a specific individual. Having an open conversation, I believe adds to a culture of being open to discussions for feedback. Depending on the response, would work together with the coworker to identify means or ways that can reduce/remove the discomfort and what can produce an ideal working environment. Th"See full answer

SG - "Clarifying questions - Alexa HW, Alexa SW, Alexa particular feature? Assumption - Pick any. Picking HW due to relevance with my background. Any particular pain point that we are trying to address, or any specific goal that I should be aware of? Assumption - None. Mine to pick. Goal for Amazon is to be the most customer centric company. To extend the same vision - With Alexa HW our goal is to provide the best customer experience possible. **Restating problem state"See full answer

Stanislav I. - "First, take a BIG short position in Tesla stocks!"See full answer

Clayton P. - "I've watched all the ML Systems designs interviews and this solution provides a clean baseline for predicting ETA using historical averages, but it falls short of addressing the broader problem of route planning. The system predicts ETA for a given segment and time interval, but it doesn’t explain how to compute the ETA for an entire route or how to integrate this into dynamic path selection. It also lacks depth on handling real-time data, adapting to distribution shift, or reacting to sudden"See full answer