Wesfarmers AI Engineer Interview Questions
The questions to prepare for a Wesfarmers AI Engineer interview. Questions from real interview reports rank first. Updated daily.
Define offline and online metrics for chatbot quality, safety, latency, reliability, cost, and hallucination control.
Explain how HNSW, IVF, PQ, and disk-based indexes trade recall, latency, memory, and build cost at embedding scale.
Explain how to design reliable, cost-efficient LLM serving for high-throughput enterprise workloads.
Compare batch and real-time inference designs for a personalized recommendation engine at Intuit.
Design a safe continual-learning loop that uses user interactions for fine-tuning without catastrophic forgetting.
Design a recommendation engine that adapts suggestions immediately after each user action.
Design a feature store that keeps batch training and real-time inference consistent, fresh, reliable, and cost-effective.
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Tests ownership, debugging judgment, and communication when a model passes evaluation but fails in production.