AI QA Engineer: Data Labeling & Model Evaluation
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Summary
Designs test cases, labels data, and evaluates AI model predictions to improve data quality and model performance. Works alongside ML engineers and product teams, maintaining structured testing documentation and proposing concrete improvements for AI-driven systems.
Crossing Hurdles is seeking a diligent QA professional to validate AI outputs through structured testing and documentation. You will design test cases, label data, and evaluate model predictions to drive continuous improvement.
Collaborating with ML engineers and product teams, you will refine testing methods for AI-driven systems, maintain thorough records, and propose concrete actions to enhance data quality and model performance.