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Segmentation
Fine-tuningPARETO.AI – Data Trainer. Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other, Internal, and Proprietary Tooling. Education includes Bachelor of Science, University of Lagos (2021). AI-training focus includes data types such as Image, Video, and Text and labeling workflows including Segmentation, Fine-tuning, and Evaluation.
TextReviewed LLM fact-checking outputs and verified claims against reputable sources. Provided structured feedback to annotators or model teams to improve response quality. Facilitated weekly recalibration meetings to align labeling decisions and reduce variance. • Fact-check verification with sources • Structured feedback generation • Weekly recalibration facilitation • Consistency improvements for LLM outputs
ImageSegmentationPerformed large-scale computer vision image and video annotation according to client labeling guidelines. Partnered with QA teams to surface edge cases and refine annotation standards. Delivered onboarding and refresher training to improve labeler accuracy and output consistency. • Image/video annotation per guidelines • QA collaboration for edge-case handling • Training development and refreshers • Improved productivity and reduced error rates
TextFine-tuningLed onboarding and upskilling for a large pool of LLM annotators to support ongoing AI training workflows. Assessed annotator performance metrics to identify skill gaps and provided targeted coaching. Maintained evolving training documentation as models and client requirements changed. • Annotator onboarding and upskilling • Performance-metric based coaching • Training documentation updates • Large-scale LLM training support
TextConducted audits of large-scale LLM datasets to ensure dataset quality remained above defined thresholds. Facilitated calibration sessions to reduce subjectivity and improve labeling consistency across annotators. Validated linguistic accuracy of model outputs to support downstream ML training. • Large-scale LLM dataset auditing • Calibration sessions for consistency • Linguistic accuracy validation • Quality score management
Bachelor of Science, Fisheries
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