DDD believes talent has no boundaries--and opportunities shouldn’t either. In 2001, we saw the need to bring tech skills and living-wage work to men and women in underserved communities in Asia. It was here that DDD helped plant the seed for a socially responsible outsourcing practice known as impact sourcing.
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We are seeking disciplined, detail-oriented professionals to work with 3D LiDAR data for machine learning and autonomous vehicle development. You will contribute to training high-precision perception models by producing consistent, accurate annotations.
Key Duties and Responsibilities
Data Annotation: Accurately label and annotate datasets (images, video, text, LiDAR, etc.) in line with project guidelines and client requirements.
Quality Assurance: Consistently check and validate work to ensure data accuracy. Demonstrate readiness to transition into a QA role as project needs evolve.
Tool Proficiency: Efficiently use various data annotation platforms and software tools to complete assigned tasks.
Documentation: Maintain clear and detailed annotation records, highlighting ambiguities and challenges encountered.
Collaboration: Work closely with team members, supervisors, and cross-functional units to ensure shared understanding and consistency in project execution.
Feedback Integration: Actively engage in training, implement feedback, and continuously refine annotation quality and speed.
Continuous Learning: Stay informed on evolving AI/ML annotation tools, methods, and best practices to enhance performance.
Time Management: Plan and prioritize tasks effectively to meet productivity goals and project deadlines.
Qualifications
Minimum Requirements:
Minimum 2 years of hands-on experience with LiDAR data annotation, 3D data labeling, or AV datasets.
Proficiency with AV annotation tools
Strong understanding of geospatial concepts, remote sensing, and 3D mapping.
Close attention to detail and accuracy.
Ability to follow structured guidelines and adapt quickly to client updates.
Strong communication and teamwork skills.
Diploma or Degree in Computer Science, Data Science, Information Technology, or related technical field.
Certification in Data Annotation, 3D Mapping, Remote Sensing, or Machine Learning is an added advantage.
Training or coursework in 3D visualization, spatial analysis, or autonomous systems
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