Marlabs AI Engineer Interview Questions
The questions to prepare for a Marlabs AI Engineer interview. Questions from real interview reports rank first. Updated daily.
Explain a production RAG pipeline and techniques for reducing unsupported or fabricated answers.
Explain multi-agent architectures, coordination patterns, tool use, evaluation, and safeguards for hallucination and prompt injection.
Explain when fine-tuning beats advanced prompting and embeddings, considering quality, cost, latency, maintenance, and safety.
Allow or reject Axis Max Life Insurance LLM requests using a per-user sliding-window rate limiter.
Design a monitoring and retraining strategy to detect and mitigate data drift in a deployed ML model.
Compare embedding models for semantic retrieval using relevance, latency, dimensionality, language coverage, and operational constraints.
Design a practical framework for comparing LLM quality, reliability, latency, cost, and safety in production.
Design an LLM serving architecture that manages long generation latency, GPU efficiency, reliability, and model quality.
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