Bounding Box Video Annotators

0 years

3 - 4 Lacs

india

Posted:1 day ago| Platform: Linkedin logo

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Skills Required

video ai training data vision labeling learning model development robotics analytics power tracking analysis annotation ids truncation lighting export json integrity consistency tooling collaborative metrics ml visual

Work Mode

Remote

Job Type

Contractual

Job Description

Industry & Sector:

AI training-data and computer vision data-labeling services supporting machine learning and perception model development across autonomous systems, robotics, retail analytics, and surveillance. We deliver high-quality annotated video datasets that power object detection, tracking, and behavior-analysis pipelines.

Standardized Title (best-performing):

Video Annotation Specialist (Bounding Box — Video)

Location:

Remote (India)Role & Responsibilities
  • Create precise frame-by-frame bounding-box annotations and maintain consistent object IDs across video sequences using industry annotation platforms.
  • Apply detailed labeling guidelines to tag objects and attributes (e.g., occlusion, truncation, pose, class) across diverse scenes and lighting conditions.
  • Perform self-review and address QA feedback, correct annotation errors, and escalate ambiguous cases to leads for resolution.
  • Export and validate annotation deliverables in required formats (COCO, YOLO, KITTI, JSON) and ensure file integrity and consistent metadata.
  • Log edge cases and propose guideline clarifications to improve annotation consistency and reduce rework.
  • Meet throughput and accuracy KPIs for daily/weekly annotation targets while upholding quality standards.

Skills & Qualifications

Must-Have

  • Bounding box annotation
  • Object tracking
  • CVAT
  • COCO format

Preferred

  • Labelbox
  • YOLO format
Benefits & Culture Highlights
  • Fully remote, India-based role with flexible working hours to accommodate throughput targets.
  • Structured QA feedback loops, role-specific training, and opportunities to upskill in annotation tooling and computer-vision workflows.
  • Collaborative, metrics-driven environment focused on data quality and scalable ML operations.
Interested candidates should be comfortable working remotely, have strong attention to visual detail, and be ready to deliver consistent, high-quality labeled video assets for production ML pipelines.
Skills: training,pipelines,throughput,annotation,data,object tracking,box,video

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