IgniteTech AI Engineer Interview Questions
The questions to prepare for a IgniteTech AI Engineer interview. Questions from real interview reports rank first. Updated weekly.
Design a feature store that lets research teams define, reuse, and serve consistent ML features across training and inference.
IgniteTechDesign an LLM serving system that balances latency, cost, scalability, and safety for production traffic.
IgniteTechDesign a prompt strategy and evaluation plan for consistent LLM API outputs under tight latency, cost, and hallucination constraints.
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Tests implementation skills for embedding-based retrieval and ranking logic.
IgniteTechExplain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.
IgniteTechChoose a decision threshold for a classifier using precision, recall, calibration, and confusion matrix tradeoffs.
IgniteTechTests language understanding and attention to detail for NLP-related tasks.
IgniteTechExplain how to train and evaluate a classifier when the positive class is rare and accuracy is misleading.
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