LiDAR Data Annotator - 3D Point Cloud Labeling & QA

Sequential Technologies International; Legazpi; On-site; PHP 350,000 - 600,000; Full time

Job summary

Sequential Technologies International is seeking a meticulous LiDAR Data Annotator to join our AI Operations team in Legazpi. You will analyze, label, and segment complex 3D point cloud data from LiDAR sensors to train autonomous systems and spatial AI applications.

The role emphasizes 3D bounding box annotations, semantic segmentation, and cross-checking with camera data, requiring strong spatial awareness and centimeter-level precision.

Qualifications

• 1–3+ years of hands-on experience annotating 3D LiDAR point clouds or multi-modal sensor datasets.
• Experience with industry-standard 3D annotation platforms is preferred.
• Strong spatial reasoning and attention to centimeter-level accuracy.

Responsibilities

• 3D Point Cloud Labeling: perform 3D bounding box annotations (cuboids), semantic segmentation, and polyline tracking on multi-sensor fused dataset (LiDAR, Radar, Camera).
• Sensor Fusion Alignment: cross-reference 3D LiDAR point clouds with 2D camera footage to ensure accurate depth perception, object detection, and tracking consistency.
• Quality & Accuracy: consistently meet or exceed strict accuracy benchmarks across complex edge cases.
• Tooling Feedback: test internal or third-party annotation platforms and report bugs, edge cases, or UX enhancements to machine learning engineers.
• Edge Case Analysis: identify, flag, and document edge cases for review by QA leads and ML researchers.
• Collaboration: participate in calibration sessions to align on ambiguous edge cases and updated labeling guidelines.

Skills

LiDAR data annotation

3D spatial reasoning

Attention to detail

Tools

CVAT

Scale AI

Labelbox

Kili Technology

Appen

Deepen AI

Playment

CloudCompare

MeshLab

ROS (rviz)

3D Bounding Box Editors

Job description

Sequential Technologies International is seeking a meticulous LiDAR Data Annotator to join our AI Operations team in Legazpi. You will analyze, label, and segment complex 3D point cloud data from LiDAR sensors to train autonomous systems and spatial AI applications.

The role emphasizes 3D bounding box annotations, semantic segmentation, and cross-checking with camera data, requiring strong spatial awareness and centimeter-level precision.