AI and Machine Learning Background Questions
A synopsis of applied artificial intelligence and machine learning experience including models, frameworks, and pipelines used, datasets and scale, production deployment experience, evaluation metrics, and measurable business outcomes. Candidates should describe specific projects, roles played, research versus production distinctions, and technical choices and trade offs.
HardTechnical
0 practiced
Your team proposes online learning for personalization to reduce drift, but engineering warns of instability and label bias. As PM, propose an experiment framework including safe guardrails, metrics for stability, how to measure label bias, and a rollback plan in case online updates degrade metrics.
EasyTechnical
0 practiced
Describe three common data quality issues you would look for when assessing a new dataset intended for a production ML feature. For each issue (for example: missing labels, label leakage, schema drift) describe a concrete mitigation that you would prioritize as PM, including any product-level changes needed to collect better data.
MediumSystem Design
0 practiced
Given: event ingestion at 50k events/minute, daily retention of 30 days, and requirement to retrain a personalization model daily with 24-hour freshness, design data pipeline requirements that balance cost and latency. Specify storage format, batch vs streaming choices, compute scheduling, and how you would measure freshness SLA.
MediumTechnical
0 practiced
Describe a practical audit plan to evaluate fairness across demographic groups for a production ML model. Include the datasets and sampling strategy needed, fairness metrics you would compute, thresholds for action, and how you would present findings and proposed remediations to executives and legal.
EasyTechnical
0 practiced
You inherit a binary classification fraud model. Explain precision, recall, F1, and ROC-AUC in product terms (user/business impact). If false positives are costly (e.g., blocking legitimate users), which metric would you prioritize and how would that affect thresholding and downstream flows?
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