Interview questions
Stripe AI engineer interview questions (2026)
6 real interview questions reported by engineers who interviewed at Stripe, spanning Data Engineering, ML Engineering, Software Engineering. Every question is scored against a golden answer on the things Stripe actually grades, architecture, token efficiency, security and correctness, not just whether your code runs.
Stripe ML Engineering questions
- Drift Detection — Building the Monitoring Pipeline for a Credit Model
You deployed a credit-scoring model 8 months ago and need an automated system that catches drift before it hurts business metrics, but true labels arrive with a 90-day lag. Design
- Drift Detection — Covariate Shift vs Concept Drift
Your model performance is degrading. Distinguish covariate shift, label shift, and concept drift with a concrete example of each; for each say whether retraining on fresh data fixe
Stripe Software Engineering questions
- TDD — Write Tests First for a Money Allocation Function
Practice test-driven development. Implement allocate(total_cents, weights) that splits an integer number of cents across N buckets proportional to weights so parts are integers and
- TDD — Tests First for a Retry Policy with Idempotency
Practice TDD. Implement should_retry(status_code, attempt, idempotency_key) plus a backoff generator, retrying only safe cases and never exceeding max attempts. First write failing
Stripe Data Engineering questions
- Seven Day Rolling Average Daily Active Users Including Zero Days
Write a single SQL query that returns the 7-day rolling average of daily active users (DAU) from a logins table, including calendar days with zero activity. ## Input - `logins(us
- DBT Model Performance Degradation: Diagnosis and Optimization Strategy
A nightly dbt model is now taking 4 hours and missing its SLA. Walk through how you would diagnose and fix it.
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