Netflix Interview Questions
Practice 106 real Netflix interview questions for 2026 — Netflix interview questions tailored for high-impact engineering and data roles. Covers all top categories — Coding & Algorithms, System Design, Behavioral & Leadership, Analytics & Experimentation, and Data Manipulation (SQL/Python). Real questions from actual interviews with detailed solutions to power your interview preparation and sharpen the problem types Netflix favors. Expect a coding- and design-heavy process: Software Engineer loops dominate, followed by Data Scientist, Machine Learning Engineer, and Data Engineer screens. For Software Engineers (42 questions) the emphasis returns again and again to ads-platform design (frequency capping, demand-side schemas, ad data models), product-facing rendering and deduplication for the homepage, concurrent systems and latency-percentile tracking, plus algorithm problems on trees, graphs and sliding-window arrays. Data Scientists (28) focus on causal inference and experiment analysis (ATE/ITT/TOT/LATE, noncompliance), ranking A/B tests, conversion propensity models and SQL retention cohorts alongside core probability. Machine Learning Engineers (7) test ML platform and scheduling design plus transformer/tokenization fundamentals; Data Engineers (3) emphasize reliable click aggregation, config rollout strategies, and search/JSON-path implementations. Prepare by practicing representative coding problems, system designs, experiment writeups, and clear metric-driven stories.
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Design Rolling-Window Ad Frequency Capping
Design a frequency-capping service for an advertising platform. The ad platform receives ad requests for users and must decide whether a candidate ad,...
Compare Losses and Explain LoRA
ML Fundamentals: Loss Functions and Low-Rank Adaptation This is a rapid-fire ML fundamentals screen. You are expected to reason precisely about loss f...
Design demand-side ads relational tables
You are designing the core relational data model for a demand-side advertising system. Create a normalized schema (tables + key columns + relationship...
Explain self-attention, LoRA, Adam vs SGD, ViT
Answer the following ML/Deep Learning interview questions: 1) Describe self-attention in Transformer models. What are the queries, keys, and values, a...
Model Direct-Sold DSP Orders
Design a data model for tracking a direct-sold demand order in a demand-side advertising platform. Context: - The platform manages advertiser demand a...
Design an Ad Frequency Capping System
Design a frequency capping system for an advertising platform. A frequency cap limits how many times a user can be shown an ad, campaign, line item, o...
Model data for an ads platform
Design a data model (logical schema) for an advertising platform. Include core entities such as: - Business/account (advertiser) - Campaign and budget...
Compute ITT, TOT, and LATE with noncompliance
In the same personalization experiment, not everyone assigned to treatment actually receives personalization (noncompliance). You are given user-level...
Design viewport dedup for Netflix home page
Design viewport dedup for Netflix home page Design the Above-the-Fold Deduplicated Home Page Rendering Context You are designing the initial viewport ...
Show role fit using past ad experience
In a manager interview for an ads engineering role, you’re often evaluated on whether you can “join and immediately contribute.” How would you: - Map ...
Design homepage viewport rendering with deduplication
This question evaluates system architecture and backend–client design competencies, including viewport-based fetching, cross-module deduplication, pag...
Model ads demand data for reporting
This question evaluates competencies in data modeling, ETL/ELT pipeline design, analytics warehousing, handling slowly changing dimensions, and high-v...
Design a robust conversion propensity model
Daily Notification Propensity Model (Top-20% Targeting) Context You need to score users once per day with the probability they will make a purchase wi...
Compute Earliest Completion Times
You are given n tasks numbered from 0 to n - 1. Each task i has a positive duration duration[i]. You are also given a list of prerequisite relationshi...
How would you support ML stakeholders?
You are an ML infrastructure engineer working closely with a data scientist stakeholder. Discuss how you would handle the following situations in a pr...
Design an ML Platform Portal
This question evaluates design and engineering skills for building an end-to-end machine learning platform, including experiment tracking, model regis...
Design a concurrent latency percentile tracker
This question evaluates understanding of concurrent data structures, thread-safety, time-windowed metrics aggregation, and percentile computation for ...
Return the longest contiguous subarray with all distinct values
This question evaluates a candidate's understanding of array-processing algorithms, duplicate detection, and maintaining state to identify the longest...
Design Netflix viewport deduplication
Design Netflix viewport deduplication Design an Algorithm to Ensure No Duplicates in the First Netflix Home-Page Viewport Context You are rendering a ...
Design a crash-resilient file system
Prompt Design a resilient file system that can recover file contents correctly after a system crash (e.g., power loss / kernel panic). The interviewer...