Computer Vision Data Annotation Specialist

Role Overview Help improve hand-tracking and pose-estimation AI by producing reliable visual training data. This contract role focuses on precise annotation of hand landmarks in images and video, supporting next-generation computer vision systems. Prior AI experience is not required. Key Responsibilities Review and annotate images and video frames, identifying hand-pose landmarks including wrists, finger joints, and fingertips. Accurately distinguish left and right hands across varied scenarios. Identify, flag, and document edge cases, including occlusion, motion blur, gloves, multiple hands, and low-light conditions. Follow detailed annotation guidelines and quality rubrics to maintain reliable, consistent data. Maintain strong accuracy and productivity while working with large computer vision datasets. Escalate ambiguous or challenging cases for clarification and perform quality-assurance reviews of previously annotated data when needed. Qualifications Experience annotating images or video for machine-learning or AI projects is preferred. Proficiency with annotation platforms. Strong attention to detail, spatial reasoning, and ability to follow complex visual instructions. Basic familiarity with computer vision concepts such as landmarks, bounding boxes, confidence scores, and ground-truth labels. Experience with hand or human-pose estimation datasets or frameworks is preferred. Background in gesture recognition, sign language, AR/VR hand tracking, or related datasets is valued. Excellent written and spoken English skills for documenting findings and collaborating remotely. Work Terms Independent contractor engagement. Open to candidates located in Northern America, Latin America, or Europe. Compensation $21 to $70 per hour. #J-18808-Ljbffr SaidGig