ppbJob Title: /b Computer Vision Annotatorbr/bLocation: /b Remote (Worldwide)br/bJob Summary: /b The bComputer Vision Annotator /b is responsible for accurately labeling and annotating image and video data to support the development and training of computer vision and machine learning models. This role plays a critical part in improving model performance by creating high-quality datasets used for object detection, image classification, segmentation, tracking, and other visual recognition tasks.br/ /ph3Responsibilities /h3ulliPerform high-precision annotation on visual data using specialized tools. Tasks include: /liliDrawing accurate bounding boxes, polygons, and polylines around objects of interest. /liliPlacing key points for pose estimation or landmark detection. /liliCreating 3D cuboids and annotating point cloud data for spatial awareness applications (e.g., autonomous vehicles, robotics). /liliConducting semantic/instance segmentation to label every pixel in an image. /liliInterpret complex labeling taxonomies and project specifications. Identify ambiguous cases and collaborate with project managers and data scientists to refine annotation guidelines for clarity and scalability. /liliUtilize advanced features of annotation tools such as CVAT, Label Studio, 3D Slicer, or Amazon SageMaker Ground Truth. Provide feedback to engineering teams to improve tool functionality and workflow efficiency. /liliProactively identify challenging data patterns, edge cases, and potential biases in datasets. Escalate these findings to help improve model robustness and mitigate bias.



/liliContribute to the development of annotation best practices, workflow optimizations, and training materials for new annotators. /liliAssist in basic data preparation tasks such as resizing images, converting data formats, or ensuring sensor data synchronization (e.g., time-stamp alignment for video and LiDAR). /liliAssist in tracking key performance insights (KPIs) such as annotation throughput, precision, and recall. Participate in calibration sessions to ensure consistency across the team.br/ /li /ulh3Requirements /h3ulliMinimum of 2 years of experience in data annotation, data labeling, or quality assurance specifically for computer vision or Machine Learning projects. /liliDemonstrated proficiency with a variety of annotation techniques including bounding boxes, polygons, key points, 3D cuboids, and segmentation masks. /liliExtensive hands‑on experience with industry‑standard annotation tools like CVAT, label Studio, 3D Slicer, Supervisely. /liliSolid understanding of computer vision concepts and terminology (e.g., object detection, image classification, LiDAR, point clouds). /liliFamiliarity with quality control processes such as consensus labeling, audit sampling, gold-task seeding, and inter‑annotator agreement metrics. /liliExceptional attention to detail with an unwavering commitment to accuracy and consistency. Proven ability to maintain high‑quality output even when labeling repetitive tasks. /liliStrong written and verbal communication skills in English. Ability to document workflows clearly and collaborate effectively teams and clients. /li /ul /p #J-18808-Ljbffr

📌 Computer Vision Annotator (España)
🏢 Odixcity Consulting
📍 España