Top 22
Prep plan
Updated weekly · Last refresh Aug 30

Whatnot AI Engineer Interview Questions

The questions to prepare for a Whatnot AI Engineer interview. Questions from real interview reports rank first. Updated weekly.

22questions
~3htotal time
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1
System DesignStart here. 8 questions · ~64 min
Design an LLM Serving PlatformHard

Design an LLM serving system that balances latency, cost, scalability, and safety for production traffic.

Cold StartFeature StoreModel ServingWhatnot
Design a Low Latency RAG PlatformHard

Design a low latency RAG system over millions of documents, with scalable retrieval, ranking, generation, and production monitoring.

low latencyscalabilityRAG architectureWhatnot
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2
Coding3 questions · ~24 min
Optimizing LLM Inference on AWSMedium

Tests coding and performance engineering for LLM inference on AWS.

performance optimizationWhatnot
Debugging Production Model DriftMedium

Tests coding and troubleshooting skills for diagnosing and mitigating model drift in production.

Machine LearningDebuggingproductionWhatnot
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3
Machine Learning4 questions · ~32 min
CI/CD for LLM EvaluationMedium

Tests ML engineering practices for automated evaluation gates and safe deployments.

CI/CDLLM EvaluationWhatnot
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4
Behavioral & Leadership3 questions · ~24 min
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5
More topics4 questions · ~32 min
Evaluating LLMs in ProductionMedium

Tests model evaluation strategy tied to real production behavior and user outcomes.

performanceLLM EvaluationproductionWhatnot
Vector Store Updates Without DowntimeHard

Tests hard system design for zero-downtime indexing and consistency in retrieval pipelines.

Whatnot
Metrics for Generated Text QualityMedium

Tests ability to define and select quality metrics for LLM outputs in production.

MetricsllmWhatnot
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The finish line: interview-readyComplete all 22 questions to finish this plan.