Project-Based Data Annotation QC Specialist – TreeD Studio

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Overview
AspiraGlobal is looking for a highly detail-oriented Project-Based Data Annotation QC Specialist to support an international road-scene data annotation project.

The role is responsible for reviewing completed annotations produced by Data Annotation Specialists using TreeD Studio, with a focus on Lane Delimiter and Road Edge annotation quality.

The QC Specialist will identify annotation errors, inconsistencies, missing information, incorrect attributes, and other quality issues before completed work is submitted for final review.

This is a project-based opportunity. Initial candidates will complete a practical assessment, with project work allocated based on quality, performance, and available project volume.

Key Responsibilities

• Review completed road-scene annotations using the TreeD Studio platform

• Perform quality checks on Lane Delimiter and Road Edge annotations

• Verify that polygon and line/polyline annotations are accurately positioned and properly formed

• Check annotated objects and road features for completeness, accuracy, and consistency

• Verify required annotation attributes and identify incorrect or missing values

• Check INSTANCE_ID consistency across image sequences

• Verify that LINE_ID values are correctly applied based on the position of the lane or road edge relative to the ego vehicle

• Review road markings, lane boundaries, curbs, guardrails, traffic cones, barriers, vegetation, and other applicable road-edge features

• Identify incorrect handling of gaps, occlusions, visible boundaries, and other special conditions

• Identify and document annotation errors requiring correction

• Provide clear feedback and correction instructions to Data Annotation Specialists

• Maintain consistent QC standards across assigned batches

• Recheck corrected annotations where required

• Escalate unclear or potentially ambiguous cases to the project team

• Maintain accurate and consistent quality throughout assigned production work

Requirements

• Excellent attention to detail and visual accuracy

• Strong ability to identify inconsistencies and errors in image-based work

• Strong ability to follow detailed technical instructions

• Comfortable working with computer-based annotation and review tools

• Good visual and spatial awareness

• Ability to evaluate repetitive image-based work while maintaining consistent quality

• Strong organizational and documentation skills

• Reliable computer and internet connection

• Ability to work independently in a remote environment

• Previous experience in data annotation, quality assurance, quality control, image labeling, LiDAR, computer vision, AI/ML data, or similar work is an advantage

• Previous experience reviewing Polygon or Polyline annotations is an advantage

• Previous experience in a QC, QA, reviewer, auditor, or team-lead role is an advantage

• Must be legally eligible to work in the Philippines

Project Assessment

• Shortlisted candidates will complete a practical assessment

• The assessment will evaluate attention to detail, visual accuracy, consistency, ability to identify annotation issues, and ability to follow project instructions

• Candidates may be asked to review sample annotation work and identify or document quality issues

• Successful candidates may be selected for ongoing project work based on demonstrated quality, performance, and project requirements

Work Setup & Project Structure

• Remote project-based work

• Philippines-based candidates

• Work performed using TreeD Studio

• Initial project scope involves quality control of Lane Delimiter and Road Edge annotation

• QC work will involve reviewing annotation output produced by Data Annotation Specialists

• Work allocation will depend on demonstrated quality and available production volume

• Additional project opportunities may become available based on performance and client requirements

Important Compensation Information

• This is a project-based engagement rather than a conventional monthly salaried position

• Compensation is based on completed project work and will be discussed with candidates selected for the project

• Work allocation and compensation are subject to project requirements, quality acceptance, and available volume