About this opportunity
Overview
Appen is hiring a Data Annotation Analyst for project-based, remote work focused on building high-quality ground-truth datasets used to train and validate perception models for autonomous and operator-assisted machines in complex real-world environments.
In this role, you’ll work with camera imagery, video, and LiDAR point clouds to produce detailed labels that support object, scene, and environment understanding. The work requires careful adherence to annotation specifications, consistent quality, and the ability to maintain output volume in a structured production setting.
What You’ll Do
- Annotate 2D and 3D objects across images, video, and LiDAR point clouds, including vehicles, machinery, people, signage, and environmental features.
- Create and maintain segmentation, object tracking, pose, and keypoint annotations across sequences.
- Apply annotation rules related to class definitions, occlusion, object thresholds, and inclusion/exclusion criteria.
- Review completed work, respond to QA feedback, and maintain quality and accuracy standards.
- Escalate ambiguous scenes, sensor artifacts, tooling issues, and specification gaps instead of making assumptions.
- Document data quality and tooling issues with clear details and reproduction steps.
- Participate in calibration sessions, guideline reviews, and team standups to support consistency.
- Share observations that help improve annotation guidelines, taxonomies, and edge-case documentation.
Requirements
- Strong attention to detail and the ability to sustain accuracy during repetitive, visually intensive work.
- Strong spatial reasoning and the ability to interpret 3D environments, including object size, position, and orientation.
- Ability to learn and navigate complex, purpose-built software and use keyboard shortcuts effectively.
- Experience working in a fast-paced, scaled environment with productivity, quality, or accuracy targets.
- Experience with image annotation GenAI workflows.
- Reliable high-speed internet, a distraction-free workspace, and the ability to work on a company-provisioned machine in a controlled environment.
Nice to Have
- Associate or bachelor’s degree.
- Experience with image, video, LiDAR, or 3D annotation tools.
- Experience in subsurface utility engineering (SUE), construction surveying, surveying, GIS, or similar spatial work.
- Experience with AutoCAD or similar tools.
- Experience in construction, mining, agriculture, industrial operations, or heavy equipment environments.
- Familiarity with point cloud data, sensor fusion, or camera-LiDAR calibration.
- Experience working with autonomous vehicles, robotics, or machine perception datasets.
Additional Information
This role is presented by Appen as part of its AI Data Opportunities project opportunities. Appen also notes that AI tools may assist parts of the hiring process, but final decisions are made by humans.
