Samuel K.

I help clients turn raw data into accurate, consistent, AI-ready datasets. With 5+ years of experience in data annotation and quality assurance, I specialize in 2D/3D LiDAR, computer vision, image and video annotation, semantic segmentation, and AI/LLM evaluation. What I bring to your project: 95%+ client-audited accuracy on LiDAR segmentation projects. 30% improvement in labeling consistency through structured QA and corrective feedback. 25% increase in project completion by helping resolve workflow bottlenecks. Services: Image annotation, bounding boxes, polygons, semantic segmentation, 3D LiDAR and point-cloud labeling, video and temporal annotation, annotation QA, dataset validation, and AI/LLM output evaluation. Tools: CVAT, Labelbox, Supervisely, Dataloop, Hasty AI, uLabel, Aurora/Lightbox, Scale AI, Pointly, BasicAI, Segments.ai, Notion, and Jira. I follow project guidelines carefully, resolve edge cases, identify inconsistencies, and deliver reliable work while minimizing avoidable rework. If you need an experienced annotator who understands both production requirements and data quality, let's discuss your project.