Airbnb Machine Learning Engineer Interview Preparation Guide - Mid Level

Airbnb's ML Engineer interview process consists of a structured multi-stage evaluation designed to assess end-to-end ML expertise, production systems knowledge, and cultural alignment. The process includes a recruiter screening call, a remote technical assessment via HackerRank, and a virtual on-site consisting of four distinct technical and behavioral rounds. Each stage focuses on different aspects of ML engineering, from hands-on coding and system design to model debugging and core values alignment. The entire process is designed to evaluate both technical rigor and collaboration in building production-grade ML systems that power Airbnb's core products like dynamic pricing, search ranking, fraud detection, and personalized recommendations.