Technical Operator- I

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, and 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.

Qualifications

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

• Working knowledge of 2D LiDAR annotation.
• Working knowledge of 3D point cloud annotation.
• Proficient working knowledge of a computer/laptop.
• Strong English reading comprehension and the 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.

Additional Information

• Familiarity with annotation tools such as CVAT, SuperAnnotate, and Labelbox.
• Understanding of ML metrics, data quality principles, and AV/ADAS ecosystems.