Image Proofreader

🎯 Key Responsibilities

Review image datasets to ensure visual quality, relevance, and annotation accuracy for Vision AI training

Flag corrupted, low-quality, or irrelevant images that could impact model performance

Identify edge cases, visual artifacts, labeling inconsistencies, or environmental variations in images

Work closely with data annotation teams to verify labeling integrity and provide feedback for corrections

Apply pre-defined visual QA guidelines and help refine those standards as the datasets evolve

Collaborate with machine learning engineers and data managers to understand model requirements and edge-case scenarios

Assist in curating high-quality training datasets for supervised learning

✅ Required Skills & Experience

Strong attention to visual detail - ability to notice subtle inconsistencies across large volumes of image data

Basic understanding of computer vision concepts and how image quality impacts model training

Experience in image review, visual QA, data labeling, or annotation validation

Familiarity with image review tools, labeling platforms, or dataset management systems (e.g., CVAT, Supervisely, Labelbox, or custom pipelines)

Ability to follow structured review processes and meet quality benchmarks

Clear communication skills to document issues and provide structured feedback

Willingness to work as per US time zone (Pacific Time).

💡 Preferred Qualifications

Prior experience supporting a Vision AI or ML training pipeline

Understanding of object detection, classification, segmentation, or video frame QA

Familiarity with edge-case review processes and model failure mode identification

Background in data ops, annotation, labeling QA, or data curation

kindly confirm if you would be interested and i can arrange next steps. Thanks