Proofreader

🔍 About the Role

We’re looking for detail-oriented Image proofreaders to play a critical role in the development and training of our Vision AI models. In this position, you’ll be responsible for reviewing, validating, and flagging issues in large volumes of image data used to train machine learning models in areas such as healthcare, safety monitoring, and autonomous systems.

Your work will directly impact the performance, accuracy, and reliability of real-world AI systems. If you have an eye for visual inconsistencies and enjoy working with data that feeds intelligent systems, we’d love to hear from you.

🎯 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

🚀 Why Join Us?

• Be a key contributor to the success of AI systems deployed in impactful domains like healthcare, safety, and supply chain automation
• Work on real-world datasets that power production-grade Vision AI models
• Flexible, friendly work environment
• Opportunity to grow in the fields of AI operations, data QA, and computer vision

📩 Apply Now

If you're passionate about quality, precision, and working at the intersection of human insight and machine learning, apply today with your resume and any relevant experience with image datasets or annotation workflows.

Have any further questions or need help? Feel free to drop me a message on here.