QA Annotation

QA Annotation (LiDAR / 2D / 3D Image Data)

Location: Banagalore

Job Type:

Note: This role is work from office 5 Days

Freshers can also apply for this role but candidate should have good knowledge into the skills set

Salary for this role is 3.75 lpa fixed not more than that.

Location Bangalore

kindly share your resume on Wassup : 8655799183 or you can refer to your friend

Role Overview:

QA Annotation Specialist

Key Responsibilities:

• Perform

  quality checks

  on LiDAR point cloud annotations, 2D bounding boxes, polygons, semantic segmentation, and 3D cuboids.
• Validate annotated data against

  guidelines, ground truth, and project requirements

  .
• Identify and correct labeling errors, inconsistencies, or deviations.
  
• Provide

  feedback and training

  to annotation teams for continuous improvement.
• Maintain high annotation quality metrics across projects.
  
• Document

  QA findings, reports, and corrective actions

  .
• Collaborate with project managers and engineers to improve annotation tools and workflows.
  
• Ensure timely delivery of QA-approved datasets.
  

Required Skills & Competencies:

• Strong knowledge of

  annotation techniques

  : 2D bounding boxes, polygons, semantic segmentation, keypoints, LiDAR point cloud labeling, and 3D cuboids.
• Hands-on experience with annotation/QC tools (e.g.,

  Labelbox, Supervisely, Voxel, CVAT, Scalabel, Segment Anything, or in-house tools

  ).
• Good understanding of

  computer vision concepts, autonomous driving datasets, and LiDAR sensors

  .
• High attention to detail and ability to spot minute errors.
  
• Ability to work with

  large datasets

  efficiently.
• Strong communication and documentation skills.
  
• Basic knowledge of

  AI/ML dataset preparation workflows

  is a plus.

Qualifications:

• Bachelors degree / Diploma in

  Computer Science, Data Science, Engineering, or related fields

  .

• 1 to 8 years of experience

  in annotation or QA for LiDAR / 2D / 3D datasets (preferred).
• Freshers with relevant

  annotation experience & training

  may also be considered.