Data Annotation Analyst

Accountabilities:: 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 visual sequences. Apply detailed annotation specifications covering class definitions, occlusion rules, object thresholds, and inclusion or exclusion criteria. Review completed work, respond to QA feedback, and consistently meet established quality and accuracy standards. Identify and escalate ambiguous scenes, sensor artifacts, tooling problems, and gaps in annotation specifications rather than making assumptions. Document data quality and tooling issues clearly, including relevant details and reproducible steps. Participate in calibration sessions, guideline reviews, and team standups to maintain consistent interpretations across the annotation team. Share observations and edge cases that can improve annotation guidelines, taxonomies, and documentation. Maintain expected production volume while ensuring annotations remain accurate, consistent, and reliable. Requirements: Strong attention to detail and the ability to maintain accuracy during repetitive, visually intensive work over extended periods. Strong spatial reasoning skills, including the ability to interpret 3D environments and understand object size, position, orientation, and relationships. Ability to learn and navigate specialized software efficiently, including keyboard shortcuts and other productivity features. Experience working in a fast-paced, scaled environment with defined productivity, quality, or accuracy targets. Experience with image annotation or GenAI data workflows. Reliable high-speed internet and a distraction-free workspace suitable for focused, visually intensive work. Ability to work on a company-provided machine within a controlled technical environment. Associate or bachelor's degree is a plus. Experience with image, video, LiDAR, or 3D annotation tools is preferred. Background in subsurface utility engineering, construction surveying, surveying, GIS, or other fields involving spatial interpretation of physical environments is advantageous. Experience with AutoCAD or similar technical design tools is a plus. Experience in construction, mining, agriculture, industrial operations, or heavy equipment environments is beneficial. Familiarity with point cloud data, sensor fusion, or camera-LiDAR calibration is preferred. Experience working with autonomous vehicles, robotics, or machine perception datasets is an advantage. Benefits: Opportunity to contribute to advanced AI and computer vision applications across complex real-world environments. Flexible working environment designed to support different working styles and team needs. Access to specialized tools, resources, and opportunities to develop technical capabilities. Collaborative culture focused on innovation, accountability, curiosity, and high-quality AI solutions. Opportunity to work alongside experienced professionals on challenging AI training and evaluation projects. Remote work environment with the flexibility to work from a suitable location in the United States. Company-provisioned machine and controlled work environment for performing annotation tasks.