Results-driven Video Data Annotator | Egocentric POV & AI/Computer Vision Specialist
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I am a results-driven Video Data Annotator with extensive experience in labeling, segmenting, and generating high-quality video datasets for artificial intelligence and computer vision models. My expertise spans both traditional video annotation and egocentric (first-person POV) video data collection for embodied AI and robotics applications. I excel at ensuring accuracy and consistency with project guidelines, performing quality assurance, and optimizing processes to deliver reliable training data for machine learning systems. I have a proven track record of recording high-quality first-person POV videos of everyday tasks using head-mounted smartphone setups in real residential environments, generating authentic raw data for computer vision and embodied AI training. Additionally, I've produced diverse egocentric video datasets focused on human-object interaction and hand movements to support downstream video annotation and Vision-Language-Action (VLA) model development. I am adept at labeling and segmenting diverse video datasets to train computer vision models, conducting quality assurance reviews, and contributing to process optimization through analytical feedback and cross-functional collaboration.
The tester documented an access blocker and submitted multiple evidence files, but the core flows could not be tested. The report lacked the requested narrated recording, device/browser details, severity, and fully structured reproduction steps with expected versus actual behavior.
Sazabi App – Core Flows QA · Jul 30, 2026