Accenture España AI Engineer Interview Questions
The questions to prepare for a Accenture España AI Engineer interview. Questions from real interview reports rank first. Updated daily.
Explain how to evaluate a regression model using error metrics, validation, and residual analysis.
Explain which classification metrics to use and how metric choice depends on the business objective and error tradeoffs.
Reduce hallucinations in a RAG system even when retrieval is already correct, using grounding, verification, and evaluation.
Explain a practical approach to fine-tuning an LLM for a specific task, including data, evaluation, and hallucination risks.
Design an end-to-end product recommendation system for a large e-commerce marketplace with strict latency and freshness needs.
Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.
Explain the transformer architecture and why it became a core building block for modern NLP systems.
Key pipeline considerations for deploying an ML model into production, including orchestration, reproducibility, data quality, and monitoring.
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