Motivation for Airbnb and Role Understanding Questions
Candidate's motivation for joining Airbnb and their understanding of the role, including alignment with Airbnb's culture, values, and product domain, to assess fit during the interview process.
EasyTechnical
0 practiced
Explain what you expect the core responsibilities of a Machine Learning Engineer at Airbnb to be. Include typical parts of the ML lifecycle you would own, the technology stack you expect to use, and how you would collaborate with data scientists and software engineers.
HardTechnical
0 practiced
Airbnb plans to deploy an ensemble of ranking models that update hourly. Design the orchestration system: how models are trained and validated, how changes are atomically swapped in serving, how feature staleness is managed, rollback strategies, and how to control cost for hourly updates.
MediumTechnical
0 practiced
Describe how you would assess data quality for historical booking logs used to train a city-level demand forecasting model. Which checks and preprocessing steps would you run to detect anomalies, and how would you handle missing or inconsistent data?
HardTechnical
0 practiced
Design a governance framework for model explainability and user recourse at Airbnb. Include risk tiers for models, explainability thresholds, logging and audit requirements, and an escalation flow for users who contest automated decisions that materially affect them.
HardTechnical
0 practiced
You inherit a legacy ML training pipeline with poor reproducibility and frequent production bugs. Propose a refactor plan that minimizes disruption while improving reproducibility, including tests, CI/CD, artifact versioning, and a migration path to the new pipeline.
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