Remote opportunity at
Appen3D & LiDAR Data Annotation Analyst
Appen is recruiting a Data Annotation Analyst to produce labelled ground truth for training and checking perception models for self-driving and operator-assisted equipment. The job is…
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About This Role
Appen is recruiting a Data Annotation Analyst to produce labelled ground truth for training and checking perception models for self-driving and operator-assisted equipment. The job is remote. The analyst labels camera frames, video and LiDAR point clouds, producing exact annotations that let perception systems identify vehicles, equipment, people, signs, ground conditions and surroundings. Responsibilities include annotating 2D and 3D objects, creating masks, tracking of objects, and pose and keypoint labels…
Job Description
Appen is recruiting a Data Annotation Analyst to produce labelled ground truth for training and checking perception models for self-driving and operator-assisted equipment. The job is remote. The analyst labels camera frames, video and LiDAR point clouds, producing exact annotations that let perception systems identify vehicles, equipment, people, signs, ground conditions and surroundings.
Responsibilities include annotating 2D and 3D objects, creating masks, tracking of objects, and pose and keypoint labels across sequences, and applying written guidelines covering class definitions, occlusion, size thresholds and inclusion criteria. The analyst checks their own output, acts on quality feedback, and reports ambiguous scenes, sensor faults, tooling problems and specification gaps instead of guessing. Joining calibration meetings, guideline reviews and daily standups is expected, along with logging data quality issues and reproduction steps.
The posting asks for keen attention to detail, the endurance to do repetitive, visually demanding work over long stretches, and good spatial reasoning to read size, position and orientation in three-dimensional scenes. Learning purpose-built software and working quickly through keyboard shortcuts are required, as is comfort in a fast-paced setting with productivity and accuracy goals. Dependable high-speed internet and a quiet workspace are needed, and the work runs on a company-supplied machine in a controlled environment. The company reports more than three decades of supplying AI training data for generative AI, LLMs, vision and speech work.
Responsibilities
- Label 2D and 3D objects across pictures, footage and LiDAR point clouds
- Make masks, track objects, and add pose and keypoint labels across frame sequences
- Follow guidelines on class definitions, occlusion, thresholds and inclusion rules
- Check your own output and act on quality feedback to keep standards high
- Flag ambiguous scenes, sensor faults, tooling issues and spec gaps rather than assume
- Log data quality and tooling problems with clear steps to reproduce them
- Attend calibration meetings, guideline reviews and daily standups
- Recommend changes that improve guidelines, taxonomies and edge-case notes
Requirements
- Sharp attention to detail that holds up through repetitive, visually intense work
- Spatial reasoning for interpreting size, position and orientation in 3D environments
- Capacity to learn complicated, purpose-built software and adopt keyboard shortcuts
- Experience in a fast-paced, large-scale setting with productivity, quality or accuracy targets
- Background with image annotation for generative AI workflows
- Reliable fast internet, a quiet workspace, and a company-issued computer used in a controlled setup
Qualifications
- An associate-level or bachelor-level degree
- Experience using tools that annotate images, video, LiDAR or 3D data
- Background in subsurface utility work, construction surveying, GIS or other spatial fields
- Familiarity with AutoCAD or similar software
- Work history in construction, mining, farming, industrial settings or heavy equipment
- Understanding of point cloud data, multi-sensor fusion or camera to LiDAR alignment
- Work with self-driving vehicles, robots or datasets for machine perception
Core Skills
Benefits
- Flexibility to deliver work in whatever way suits you and your team
- Tools, resources and development opportunities for building skills over time
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is the job based?
The listing says remote. The posting also asks for dependable high-speed internet and a quiet, distraction-free workspace.
Is this a full-time position?
The listing is for a full-time role.
What equipment is needed?
Work is done on a company-supplied machine inside a controlled environment.
Does the posting state pay?
No pay range or salary is given in the posting text.
Sample Interview Questions
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