TechMojo Solutions
From TechMojo Solutions's careers page
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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.
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. Responsibilities 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. Requirements Strong attention to detail and the ability to maintain accuracy while performing repetitive, visually intensive work for extended periods. Strong spatial reasoning skills, including the ability to interpret 3D environments and understand object size, position, and orientation. Ability to learn and navigate complex, purpose-built software and become productive with keyboard shortcuts and other tooling features. Experience working in a fast-paced, scaled environment with defined 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 within a controlled environment. Nice to have Associate or bachelor’s degree. Experience with image, video, LiDAR, or 3D annotation tools. Experience with subsurface utility engineering (SUE), construction surveying, surveying, GIS, or other work involving spatial interpretation of physical environments. Experience with AutoCAD or similar type 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.
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