Digital Divide Data (DDD) is a BPO that delivers ML data solutions and content services to Fortune 500 companies and the world’s leading academic institutions. DDD is unique in its ability to deliver end-to-end data creation, curation, labeling, and annotation services, regardless of scale, with a guaranteed level of quality.
Job DescriptionRole Overview
The Associate is responsible for executing 2D and 3D LiDAR annotation and segmentation tasks in accordance with defined SOPs, quality benchmarks, and productivity targets. This role requires technical precision, spatial awareness, and disciplined execution in high-volume production environments.
Responsibilities
Production & Quality Execution
Execute repetitive 2D/3D LiDAR annotation and segmentation tasks in strict adherence to SOPs
Maintain classification accuracy across object types and categories
Meet or exceed defined benchmarks for:
Productivity
Quality
Accuracy
Sustain consistency in output with minimal supervision
Issue Identification & Continuous Improvement
Identify recurring annotation errors or tool-related issues
Escalate quality risks or inconsistencies in labeling standards
Suggest improvements to tools, taxonomy, or workflow
Communication & Collaboration
Communicate effectively with peers, QA teams, and stakeholders in English
Document issues clearly and accurately
Success Profile
High attention to detail
Strong spatial and logical reasoning ability
Ability to sustain accuracy in repetitive workflows
Foundational understanding of quality control
Ability to identify misclassification and segmentation inconsistencies
Education Requirements
Diploma or higher qualification in a relevant field such as:
Computer Science
Information Technology
Engineering (Electrical, Computer, Geospatial, or related)
Data Science
Geospatial Studies
Or equivalent technical discipline
Technical Competencies
LiDAR & Segmentation Skills
Working knowledge of 2D LiDAR annotation
Working knowledge of 3D point cloud annotation
Systems & Communication
Proficient working knowledge of a computer/laptop
Strong English reading comprehension
Ability to write clear and accurate English
Ability to interpret and execute complex SOP documentation
Ability to perform basic object segmentation and classification
Understanding of bounding boxes, cuboids, and object tagging principles
Ability to follow annotation taxonomies and ontology guidelines accurately
- Familiarity with annotation tools such as CVAT, SuperAnnotate, and Labelbox.
- Understanding of ML metrics, data quality principles, and AV/ADAS ecosystems.
Skills Required
- Diploma or higher in Computer Science, IT, Engineering, Data Science, Geospatial Studies, or related technical discipline
- Working knowledge of 2D LiDAR annotation
- Working knowledge of 3D point cloud annotation
- Basic object segmentation and classification skills
- Understanding of bounding boxes, cuboids, and object tagging principles
- Proficient working knowledge of a computer/laptop
- Strong English reading comprehension and ability to write clear, accurate English
- Ability to interpret and execute complex SOP documentation
- Foundational understanding of quality control and ability to identify misclassification
- Familiarity with annotation tools such as CVAT, SuperAnnotate, and Labelbox
- Understanding of ML metrics, data quality principles, and AV/ADAS ecosystems
What We Do
Digital Divide Data (DDD) provides end-to-end AI and autonomy solutions, specializing in human-in-the-loop data annotation, validation, and ML model training. Trusted by Fortune 500 companies and government entities, DDD supports the lifecycle of autonomous systems and generative AI. Founded in 2001, the company operates on a unique social impact model, providing professional opportunities and education to talented youth from low-income backgrounds, while ensuring high-quality, reliable AI performance.
