Data Labeling & Annotation Specialist | OpenTrain AI Projects
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Data Labeling & Annotation Specialist — OpenTrain AI Projects (Video annotation for VLA model training). Brings 4+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Encord, Internal, and Proprietary Tooling. Education includes Bachelor of Arts, University of Uyo (2024). AI-training focus includes data types such as Video, Image, and Document and labeling workflows including Object Detection, Evaluation, and Rating.
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Worked as a Data Labeling & Annotation Specialist on VLA (Vision-Language-Action) model training video annotation tasks. Applied bounding boxes, segmentation masks, and keypoint labels to ensure robotics dataset frames were consistently annotated. Performed self-audits and follow guideline requirements to maintain high-quality submissions. • Labeled humanoid robotics video frames using bounding boxes, masks, and keypoints. • Ensured multi-frame consistency by maintaining accurate labels across sequences. • Reviewed and self-audited outputs against project guidelines before submission. • Supported accuracy and consistency checks to meet quality score targets.
Worked as a Technical Documentation & Content Specialist, producing structured technical documentation with high attention to detail. Managed data-driven workflows and applied consistent formatting and labeling standards across large volumes of client content. Performed quality checks to ensure documentation accuracy and consistency. • Produced structured technical documents with consistent labeling standards. • Managed data-driven workflows and quality checks for multiple client projects. • Applied consistent formatting across large volumes of content. • Maintained high accuracy and attention to detail during documentation.
Served as an AI Content Trainer and Data Reviewer for Mindrift. Evaluated AI-generated outputs for quality, accuracy, and adherence to provided guidelines. Applied structured evaluation criteria required by the role to support consistent reviewer decisions. • Assessed AI output quality against reference expectations. • Checked guideline compliance and accuracy in generated responses. • Worked within a structured AI training and review framework. • Produced reviewer judgments to support downstream model or content improvement.
Bachelor of Arts, Agricultural Economics
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