Data Annotation Specialist

Job Title: Data Annotation Specialist (2D & 3D)

Experience: 01 Years

Location: Gurgaon

Employment Type: Full-time

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:

• Bachelors 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.