Airbnb
Staff
Own the Modeling → ML Serving → API architecture rebuild for Airbnb's host pricing systems
A senior IC (Staff-level) role owning the technical strategy for a full ML serving-infrastructure rearchitecture at Airbnb — feature stores, model versioning, online/offline consistency, and backfill/evaluation infra for the Host Pricing org. Interview will be deep on ML systems design (not modeling itself), cross-team architecture contracts, and hands-on coding at senior IC scale.
Step into this interview
Free · a live voice mock calibrated to this exact role
What this interview tests
- Feature store design & online/offline consistency
- Model versioning and multi-version serving
- Backfill and evaluation infrastructure at scale
- Cross-team technical contracts (Modeling vs. Serving)
- Hands-on architecture + coding at senior IC level
Common question themes
Design a feature store that guarantees training/serving consistency
How would you support multiple model versions in a shared serving stack
Describe solving point-in-time correctness for backfills over historical data
Tell me about defining a technical contract between two teams so each could move independently
How have you driven a cross-org ML infrastructure migration and sequenced the work
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