AI Data Labeler (Computer Vision)

TL;DR

AI Data Labeler (Computer Vision): Serving as the ground truth backbone for a computer vision pipeline by annotating complex image and video data with an accent on SKU-level classification and edge case identification. Focus on auditing model predictions, documenting failure modes, and validating hardware-software performance to ensure high-accuracy product identification.

Company

hirify.global is a technology company building advanced computer vision systems for automated checkout and retail environments.

What you will do

• Label images and video frames using bounding boxes, polygons, and segmentation masks.
• Annotate challenging edge cases including occlusion, glare, and motion blur.
• Audit peer annotations and model predictions to enforce high quality standards.
• Identify and document hardware-related capture issues like poor lighting or camera misalignment.
• Collaborate with ML and hardware engineers to prioritize fixes and improve system accuracy.
• Maintain and refine internal labeling guidelines as new product packaging emerges.

Requirements

• 2+ years of experience labeling data for computer vision, robotics, or similar fields.
• Proficiency with annotation tools such as CVAT, Labelbox, or SuperAnnotate.
• Exceptional attention to detail and ability to perform repetitive, precision-oriented work.
• Strong written communication skills for documenting QA reports and edge cases.
• Ability to reason about visual edge cases from physical device captures.

Nice to have

• Working knowledge of ML evaluation metrics like precision, recall, and IoU.
• Experience with hardware troubleshooting or lab environments.
• Background in roles requiring meticulous inspection or quality assurance.

Culture & Benefits

• Opportunity to work on cutting-edge computer vision technology.
• Collaborative environment working directly with ML and hardware engineering teams.
• Focus on high-precision work with clear impact on real-world system performance.