Metrics, Guardrails, and Evaluation Criteria Questions
Design appropriate success metrics for experiments. Understand primary metrics, secondary metrics, and guardrail metrics. Know how to choose metrics that align with business goals while avoiding unintended consequences.
HardTechnical
54 practiced
Propose a metric suite and experimental protocol to quantify a model's robustness to adversarial distribution shifts across subpopulations (e.g., demographic slices, sensor types). Include how you would construct evaluation datasets, design perturbation strategies, compute worst-group and aggregated robustness metrics, and ensure sufficient statistical power to draw conclusions.
HardTechnical
64 practiced
Design a metric taxonomy and governance process for a large research organization that includes naming conventions, ownership, versioning, change control, SLAs for metric freshness, audit logging, and a review board. Discuss tooling, workflows, and incentives you would implement so research and product teams adopt the governance without stifling innovation.
MediumTechnical
77 practiced
Design experiments to evaluate the calibration of a classification or language model's confidence outputs. Include metrics such as Expected Calibration Error (ECE), reliability diagrams, Brier score, and negative log-likelihood. Explain how calibration affects downstream decisions and describe correction methods (temperature scaling, isotonic regression) and how you'd validate them.
MediumTechnical
59 practiced
You are responsible for safety guardrails that trigger human review. Define a policy that balances false positives (unnecessary human reviews) and false negatives (missed harmful outputs). Describe how you would model the costs, choose thresholds, measure reviewer workload, and iterate on thresholds with operational data.
MediumTechnical
55 practiced
You need to compare models across accuracy, latency, and energy consumption. Discuss approaches to construct composite metrics or use multi-objective evaluation, explain how Pareto frontiers are constructed and interpreted, and describe how you would select a model for deployment from the Pareto-optimal set given stakeholder constraints.
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