2D Panoptic Segmentation Annotator

Company Description IntelliScan.Africa is a U.S.-headquartered, AI-enabled BPO and data operations company specializing in secure, scalable human-in-the-loop workflows for regulated, data-intensive environments. The company supports banks, insurers, governments, and technology organizations with document intelligence, KYC/AML operations, regulatory review, and AI data preparation. By combining skilled human reviewers with structured operational frameworks and enterprise-grade quality assurance, IntelliScan.Africa helps clients modernize document-centric operations and accelerate AI initiatives. Its delivery hubs across Africa operate with strict accuracy, security, and audit standards while remaining flexible enough to scale with demand. The company is committed to building a sustainable, highly trained workforce aligned with global enterprise standards, creating long-term value for clients and communities.
Role Description The 2D Panoptic Segmentation Annotator is a full-time remote role focused on producing high-quality image annotations for computer vision and AI training datasets. Day-to-day responsibilities include labeling objects and regions in 2D images with precise segmentation masks, class labels, and instance IDs according to detailed guidelines. The annotator will review and validate annotations for consistency, follow project-specific taxonomies, and flag ambiguous or unclear cases for clarification. The role includes collaborating with team leads and quality assurance specialists, meeting productivity and accuracy targets, and using annotation tools and platforms efficiently. The annotator will also provide feedback on labeling guidelines and workflows to improve data quality and operational efficiency over time.
Qualifications

• Strong visual attention to detail and accuracy, with the ability to differentiate fine object boundaries and complex scenes.
• Experience with image annotation tools or graphic interfaces used for segmentation, bounding boxes, and labeling tasks.
• Ability to follow structured guidelines, taxonomies, and quality standards, and apply them consistently across large datasets.
• Basic understanding of computer vision or AI data preparation concepts, especially segmentation and classification workflows.
• Comfort working with digital productivity tools (e.g., web-based platforms, spreadsheets, task trackers) and learning new software quickly.
• Reliable high-speed internet connection and a suitable remote working environment to support full-time, focused annotation work.
• Strong time management skills, with the ability to meet daily targets and project deadlines while maintaining quality.
• Effective written communication skills for reporting issues, documenting edge cases, and collaborating with distributed teams.
• Prior experience in data labeling, BPO operations, quality control, or related fields is an advantage but not required.
• Relevant education or training in a technical, design, or analytical discipline is beneficial but open to candidates with demonstrated capability.