Airbnb Machine Learning Engineer Interview Preparation Guide - Staff Level
Machine Learning Engineer
Airbnb
Staff
8 rounds
Updated 11/23/2025
Airbnb's Machine Learning Engineer interview process for Staff level consists of a structured pipeline designed to assess deep technical expertise, production ML systems knowledge, leadership capabilities, and cultural alignment. The process includes an initial recruiter screening, online technical assessments, multiple phone-based technical rounds, and a comprehensive virtual on-site loop with system design, coding, production debugging, and behavioral evaluations. Staff-level candidates are expected to demonstrate mastery of ML systems at petabyte scale, architectural leadership, mentoring ability, and strategic thinking about ML platform decisions.
Interview Rounds
1
Recruiter Screening
40 min6 focus topicsbehavioral
2
Technical Assessment (HackerRank)
45 min5 focus topicstechnical
3
Phone Screen 1: ML Coding and Data Structures
60 min5 focus topicstechnical
4
Phone Screen 2: ML System Design Fundamentals
60 min6 focus topicssystem design
5
Onsite Round 1: Production ML System Design
60 min6 focus topicssystem design
6
Onsite Round 2: Advanced Model Architecture and Production Optimization
60 min6 focus topicstechnical
7
Onsite Round 3: Production ML Debugging and Incident Response
60 min6 focus topicstechnical
8
Onsite Round 4: Behavioral and Airbnb Culture Fit
60 min6 focus topicsbehavioral
Additional Information