Data Annotator

Expert Technology Services

  • Irving, TX
  • 2 days ago

    Highlights

    Conduct rigorous QA audits for labeling accuracy, semantic consistency, and temporal coherence-even in edge cases (poor visibility, complex terrain). - Proficient with 3D spatial data (LiDAR, depth maps, trajectories) and labeling tools (e.g., CVAT, Labelbox, Scale AI, Supervisely).

    Numbers & Facts

    LocationIrving, TX

    Description

    Certainly! Here's a job summary in list format based on your description for the Data Annotator & QA Reviewer (Autonomy & Robotics Mining Operations):

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    ### Job Summary

    - Perform Manual Data Annotation & QA Review
    - Annotate and QA review multi-modal data: video, images, 3D point clouds, and machine sensor data (LiDAR, radar, CAN bus).
    - Label objects, 3D spatial boundaries, trajectories, actions, task sequences, intent, and outcomes for heavy mining equipment.

    - Perception & Sensor Annotation
    - Accurately label site entities (vehicles, personnel, terrain features) across 2D video and 3D LiDAR/radar data.
    - Map and track heavy equipment trajectories, articulation, and operational states.
    - Align and cross-reference visual and sensor telemetry for temporal and spatial consistency.

    - Vision-Language-Action (VLA) Annotation
    - Decompose mining workflows into structured sequences: task action intent causation outcome.
    - Identify and annotate machine/operator intent and cause-effect chains within mining operations.
    - Tag expected vs. actual outcomes (e.g., load success, hazard encounters).

    - Quality Assurance (QA) & Data Audit
    - Conduct rigorous QA audits for labeling accuracy, semantic consistency, and temporal coherence-even in edge cases (poor visibility, complex terrain).
    - Provide structured feedback to annotators and suggest updates to labeling guidelines as edge cases are encountered.

    - Collaboration & Process Improvement
    - Work closely with cross-functional teams to maintain and improve annotation quality.
    - Update and maintain documentation and annotation schemas for evolving mining scenarios.

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    Required Experience & Skills

    - 1+ years in data annotation, labeling, or QA for computer vision, robotics, or autonomous systems.
    - Proficient with 3D spatial data (LiDAR, depth maps, trajectories) and labeling tools (e.g., CVAT, Labelbox, Scale AI, Supervisely).
    - Strong understanding of mining operations, spatial perception, and heavy equipment mechanics.
    - Attention to detail, technical aptitude, and ability to handle structured metadata (JSON/XML).
    - Strong communication skills for feedback and process documentation.

    Desired/Bonus Experience

    - Background in mining engineering, geotechnical engineering, robotics, autonomous vehicles, or industrial autonomy.
    - Familiarity with autonomous haulage systems, telemetry logs, or embodied VLA models.

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    Let me know if you want a more condensed or detailed version!

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