About the Role We’re building high-quality ground-truth datasets used to train and validate perception models for autonomous and operator-assisted machines working in complex, real-world environments. As a Data Annotation Analyst, you’ll work with camera imagery, video, and LiDAR point clouds to create precise labels that help perception systems understand objects, people, terrain, and surrounding environments. You’ll work in specialized annotation tools, following detailed specifications while balancing accuracy, consistency, and production volume. Your Impact Annotate 2D and 3D objects across images, video, and LiDAR point clouds, including vehicles, machinery, people, signage, and environmental features.
Create and maintain accurate segmentation, object tracking, pose, and keypoint annotations across sequences.
Apply detailed annotation guidelines, including class definitions, occlusion rules, object thresholds, and inclusion/exclusion criteria.
Review your work, respond to QA feedback, and maintain established quality and accuracy standards.
Identify and escalate ambiguous scenes, sensor artifacts, tooling issues, and gaps in specifications rather than making assumptions.
Document data quality and tooling issues with clear details and reproduction steps.
Participate in calibration sessions, guideline reviews, and team standups to maintain consistent interpretations.
Share observations that help improve annotation guidelines, taxonomies, and edge-case documentation. Success in this role means producing accurate, consistent annotations at the expected volume while helping maintain a reliable, high-quality dataset. What You Bring