Axsys IT Interview Questions
The questions to prepare for Axsys IT interviews, across all roles. Questions from real interview reports rank first. Updated daily.
Design an LLM serving system that balances latency, cost, scalability, and safety for production traffic.
Explain how bagging and boosting differ, and identify a representative algorithm for each ensemble method.
Approach for monitoring a model in production and spotting drift, threshold issues, and calibration loss.
Distinguish vanity metrics from metrics that drive decisions in a growth review.
Discuss how to build ML pipelines that are repeatable, traceable, and observable across training and deployment.
Explain how to validate SQL data before reporting, including null checks, duplicates, outliers, and aggregation reconciliation.
Explain a practical approach to fine-tuning an LLM for a specific task, including data, evaluation, and hallucination risks.
Explain how embeddings and vector databases fit into a retrieval pipeline for grounded AI responses.
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Combine Acxiom customer tables into one profile per customer using the most recent available attributes.
AcxiomCreate a unified Johns Hopkins University dashboard result by combining department activity, users, and targets.
The Johns Hopkins UniversityAudit claims for missing members, invalid amounts, and payment totals that exceed billed amounts.
Healthfirst (New York)
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