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.
Required Experience
Minimum 3 years of experience in autonomous vehicle data annotation.
Minimum 1 year of experience working on Vision-Language Action projects.
Experience working with complex scene understanding tasks, including: Object interactions, Agent behavior, Spatial reasoning, Action prediction, Intent interpretation, Task-sequence analysis.
Experience in review workflows, annotation guideline interpretation, and edge-case handling within production environments.
Required Skills
Strong understanding of VLA concepts, including vision-language alignment, action grounding, temporal understanding, and contextual scene interpretation.
Ability to analyze dynamic environments and accurately label or review agent actions, intent, object relationships, and task sequences.
Excellent attention to detail and strong decision-making skills in ambiguous annotation scenarios.
Ability to quickly learn project-specific guidelines, tools, workflows, and quality standards with minimal supervision.
Strong communication and collaboration skills to contribute effectively to calibration sessions, QA discussions, and reviewer feedback loops.
A disciplined and quality-driven approach to data review and annotation accuracy.
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