Data Annotation Specialist

0 years

0 Lacs

Posted:1 day ago| Platform: Foundit logo

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Job Type

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Job Description

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Job Summary:

We are seeking an entry-level Data Annotation Specialist (2D & 3D) to support our AI and Computer Vision initiatives. The role focuses on creating high-quality labeled datasets using a variety of annotation techniques across both 2D (images, videos) and 3D (LiDAR, point clouds) data.

Key Responsibilities:

  • Perform detailed annotations including bounding boxes, polygon/semantic/instance segmentation, keypoints, cuboids, and object tracking.
  • Work with 2D and 3D datasets such as images, videos, depth maps, LiDAR scans, and point clouds.
  • Use annotation tools including

    CVAT, LabelMe, Roboflow

    , Labelbox, Supervisely, and relevant 3D annotation platforms.
  • Maintain accuracy, consistency, and productivity as per project standards.
  • Review annotations for quality and correctness before submission.
  • Collaborate with engineering, QA, and data teams to refine annotation workflows.
  • Report annotation conflicts or unclear cases to improve guidelines and dataset integrity.

Required Skills & Qualifications:

  • 01 years of experience in data annotation or related tasks.
  • Understanding of annotation techniques such as segmentation, bounding boxes, polygons, and keypoints.
  • Basic familiarity with 3D data formats including LiDAR or point clouds.
  • Experience with annotation tools including Roboflow and CVAT (or willingness to learn).
  • Strong attention to detail, ability to follow complex instructions, and good communication skills.
  • Basic awareness of computer vision concepts is an added advantage

Nice-to-Have:

  • Exposure to AI/ML projects or computer vision datasets.
  • Experience with 3D annotation tools (e.g., Pointly, Segments.ai).
  • Understanding of QA processes for annotated datasets.

Education:

  • Bachelor's degree or diploma in any field. Technical degrees are preferred but not mandatory.

Why Join Us:

  • Opportunity to work directly with AI and Computer Vision teams.
  • Exposure to industry-standard annotation tools and workflows.
  • Growth pathways toward Data Operations, ML Ops, or Computer Vision roles.

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