Smartphone Screen Surface Defect Annotator

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this remote project. OpenTrain is the #1 platform for finding and building careers in AI training and data labeling, helping contributors discover projects, build experience, and apply to work shaping modern AI systems.

  • Remote work available worldwide
  • Part-time contractor opportunity
  • Free OpenTrain account and application

About AI Training and Image Annotation

AI training is the human work behind modern artificial intelligence. Contributors prepare visual examples by identifying and precisely marking objects, surfaces, and defects so AI systems can learn to recognize them accurately.

  • Work with real image data used to improve AI systems
  • Use careful visual judgment and attention to detail
  • Build experience in a fast-growing technology field

The Role

As a Smartphone Screen Surface Defect Annotator, you will work on a 200-image-sized dataset of 20 Megapixel photographs showing the front surfaces of smartphone devices. Your task is to use segmentation annotations to highlight every area containing a surface defect.

Pre-annotations are provided to support the labeling process. The work is focused on producing precise defect boundaries while preserving the distinction between damaged areas and the surrounding background.

  • Data type: Smartphone screen images
  • Annotation type: Segmentation
  • Software: Label Studio
  • Language: English
  • Experience level: Entry level

What You'll Do

You will review smartphone screen photos and annotate all visible areas affected by defects. Defect examples include scratches, pit-defects, blemishes, missing surfaces, cracks, and discolored areas.

Annotations should include all pixels belonging to each defect while excluding background pixels as much as possible. Careful boundary placement is central to the quality of this dataset.

  • Review 20MP smartphone front-screen photographs
  • Highlight scratches, pits, blemishes, cracks, missing surfaces, and discoloration
  • Refine or complete the provided pre-annotations
  • Include all defected image pixels
  • Exclude background pixels wherever possible

Requirements and Project Details

This is an entry-level project with no additional requirements listed. You should be comfortable reviewing images and creating precise segmentation annotations in Label Studio.

  • No other requirements
  • Less than 20 hours per week
  • Part-time contractor engagement
  • Pay: $2 USD per hour
  • Worldwide availability

Why Join AI Training Work

Image annotation can be a flexible way to enter the AI industry without requiring extensive prior experience. Remote projects often allow contributors to fit work around their existing schedule while directly helping improve how AI systems understand visual information.

Apply through OpenTrain to get started with this smartphone refurbishment data project and contribute to the development of more capable computer vision systems.

  • Flexible remote work from anywhere
  • Suitable for entry-level contributors
  • Part-time schedule of less than 20 hours per week
  • Hands-on experience with image segmentation
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