Dataford
Interview QuestionsInterview GuidesExperiencesMock InterviewsPricing
Get started
Dataford
Popular roles
Software EngineerData AnalystData ScientistData EngineerBusiness AnalystAI EngineerMachine Learning EngineerProduct Manager
Browse
Browse All RolesEvery role hub, from analyst to MLBrowse All CompaniesCompany-specific interview loopsAll Interview GuidesThe full guide library
Top questions by role
Software EngineerData AnalystData ScientistData EngineerBusiness AnalystAI EngineerMachine Learning EngineerProduct Manager
Top questions by skill
SQLPythonStatisticsMachine LearningA/B TestingSystem DesignGenerative AIProduct SenseMetricsBehavioral
Browse all questions →Try a mock interview
Experiences
Practice
Mock InterviewsTimed interview simulations with feedbackSuccess PathYour 6-week structured planModulesCurated lessons by topicWebinarsTalks from ex-Big Tech data leadsPlaygroundA free-form scratch editor
Learn
BlogInterview strategy and career adviceTech Job Market ReportHiring trends across data and AI rolesFor UniversitiesDataford for career centersAbout DatafordWho we are and how we build
Pricing
Build my plan

WhatsApp High-Level Design

HardSystem Design00:00
Practice interviewer
In session
5 left
00:00

Your question is WhatsApp High-Level Design. Take a moment with it on the right.

Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).

You need to log in / sign up to chat or submit.

Problem

Design WhatsApp at a high level (HLD). Asked in the R2 Senior Technical Lead stage. Explain the end-to-end architecture, then discuss how you would incorporate an ML subsystem for spam or abuse detection if ML depth is required.

Deliverables

  1. Clarify functional and non-functional requirements.
  2. Describe clients, APIs, message routing, storage, delivery, and notifications.
  3. Explain the ML pipeline, including candidate generation, ranking, re-ranking, serving, and feedback.
  4. Separate online serving from batch processing and training.
  5. Define evaluation, monitoring, privacy controls, and failure handling.

Constraints

Do not assume product metrics without asking. Make scale, latency, availability, retention, encryption, and compliance assumptions explicit before sizing the design.