PSEG AI Engineer Interview Questions
The questions to prepare for a PSEG AI Engineer interview. Questions from real interview reports rank first. Updated daily.
Explain a practical approach to fine-tuning an LLM for a specific task, including data, evaluation, and hallucination risks.
Reduce hallucinations in a RAG system even when retrieval is already correct, using grounding, verification, and evaluation.
Assesses designing coordinated agents to complete multi-step customer service workflows reliably.
Design an LLM serving system that balances latency, cost, scalability, and safety for production traffic.
Assesses building monitoring and alerting to detect drift and protect model performance over time.
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Tests approaches for chunking, retrieval, and orchestration to work within LLM context limits.
Evaluates privacy and security controls for fine-tuning on sensitive customer data.
Tests evaluating embedding models for retrieval quality, latency, and operational fit for PSEG document search.