Qa Engineer
Crossing Hurdles
Design, execute, and document test cases and scenarios to validate AI outputs against defined requirements.Review, annotate, and label data sets to enhance machine learning model training accuracy.Evaluate, analyze, and report on model predictions, identifying inconsistencies, errors, or patterns for continuous improvement.Collaborate with cross‐functional teams to communicate findings, raise questions, and clarify project requirements.Contribute to the development and refinement of testing methodologies specific to AI‐driven systems.Maintain detailed, organized records of evaluations, test results, and feedback through written documentation.Provide actionable recommendations to optimize data quality and model performance.RequirementsHands‐on expertise in software quality assurance, with a strong understanding of test planning and defect reporting.Strong relevant experience with data labeling, annotation, reinforcement learning from human feedback (RLHF), or model evaluation.Proficiency in English at B2 level or above for effective collaboration and reporting.
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