Airbnb Machine Learning Engineer (Entry Level) - Comprehensive Interview Preparation Guide
Machine Learning Engineer
Airbnb
entry
6 rounds
Updated 11/23/2025
Airbnb's Machine Learning Engineer interview process consists of 6 stages spanning initial recruiter screening, technical assessment, and a comprehensive 4-round on-site loop. The process evaluates fundamental ML knowledge, hands-on coding proficiency, system design thinking, production ML awareness, and alignment with Airbnb's core values of belonging and innovation. Entry-level candidates are assessed on foundational competency, learning ability, and potential to grow within Airbnb's ML-driven platform.
Interview Rounds
1
Recruiter Screening
40 min4 focus topicsbehavioral|culture fit
2
Technical Screen (HackerRank Assessment)
45 min5 focus topicstechnical
3
On-Site Round 1: Data Manipulation & ML Coding
50 min5 focus topicstechnical
4
On-Site Round 2: ML System Design
50 min6 focus topicssystem design
5
On-Site Round 3: Model Debugging & Troubleshooting
50 min5 focus topicstechnical
6
On-Site Round 4: Core Values & Behavioral Interview
50 min5 focus topicsbehavioral|culture fit
Additional Information