Job Summary (List Format): Data Annotator & QA Reviewer (Autonomy & Robotics)
Main Purpose:
Support the development of autonomous mining machines by executing manual data annotation, sensor data fusion, and rigorous QA review, creating high-quality datasets for advanced AI models.
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### Key Responsibilities:
- Perception & Sensor Data Annotation
- Annotate objects and features in video, images, and 3D sensor data (LiDAR, radar) related to mining environments.
- Precisely label spatial entities (haul roads, rock piles, machinery, vehicles, personnel) in both 2D and 3D data.
- Track and annotate the motion and orientation of heavy equipment in operational scenarios.
- Align and cross-reference multi-sensor data (visual, GPS/GNSS, IMU, CAN bus, hydraulic sensors) for accurate mapping.
- Vision-Language-Action (VLA) Annotation
- Decompose and label complex mining tasks into detailed actions, intents, and outcomes.
- Annotate machine/operator intent (e.g., maneuver decisions, speed adjustments) and chain of causation in operational sequences.
- Tag environmental triggers and verify expected vs. actual outcomes of mining activities.
- Quality Assurance (QA) & Audit
- Conduct high-precision QA audits of annotated datasets, focusing on edge cases (e.g., dust, poor lighting, complex terrain).
- Ensure temporal consistency and correct semantic labeling throughout data sequences.
- Provide feedback and help update labeling guidelines as new mining scenarios arise.
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### Required Skills & Qualifications:
- 1+ years of experience in data annotation, labeling, or QA for computer vision, robotics, or autonomous systems.
- Experience working with 3D spatial data (LiDAR, depth maps, multi-camera feeds).
- Familiarity with standard labeling software (e.g., CVAT, Labelbox, Scale AI, Supervisely, V7, Encord).
- Ability to analyze and structure complex heavy machinery interactions into clear task-action-intent-outcome flows.
- Comfortable handling geospatial and structured data formats (JSON, XML).
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### Key Technical & Soft Skills:
- Understanding of mining operations, heavy equipment, and pit safety.
- Strong 3D spatial visualization and attention to detail, especially in challenging visibility conditions.
- Effective communication for providing feedback and updating annotation guidelines.
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### Desired/Preferred Experience (Nice to Have):
- Background in Mining Engineering, Geotechnical Engineering, Robotics, Autonomous Vehicles, or related fields.
- Experience with autonomous haulage systems, telemetry logs, or industrial robotics VLA models.