Expert Data Annotator for Complex Engineering CT Scans (US Native)

We are seeking an elite, detail-oriented Data Annotator to join our team for a critical project involving the segmentation and classification of 2D battery slice images. This is not a simple bounding box task. You will be working with complex, rule-based guidelines to produce highly accurate and consistent annotations that are crucial for training our machine learning models. We are looking for a meticulous professional who thrives on precision and can master a complex set of instructions. Key Responsibilities: You will be responsible for two primary annotation tasks on sets of CT scan images: 1. Core Segmentation & Buckling Classification: - Perform precise polygon segmentation of the battery "core" by identifying the interior boundary of the "first cathode wrap." - Apply specific geometric rules, such as identifying start/end points based on locally minimal distances, to define the segmentation boundary. - Accurately handle and annotate complex edge cases, including cathode tip bending, delamination, boundary discontinuities, and tapering, following detailed visual guides. - Ensure all segmentation masks are smooth, clean, and accurately follow the specified contours. - Classify each image for "cathode buckling" by identifying the presence of negative curvature on the cathode coil, while correctly ignoring delamination and anode buckling. 2. Overhang Segmentation: - Create distinct segmentation masks for "cathode" and "anode overhang" components. - Follow specific inclusion/exclusion rules, labeling only the overhangs that are adjacent to or between cathode segments. - Maintain a high degree of overlap and accuracy between related masks. - Leverage the sequential nature of the dataset by efficiently labeling the first image in a series, then copying and fine-tuning subsequent images for maximum productivity. What We're Looking For (Required Skills): - Proven Expertise in Complex Segmentation: You must have extensive experience with intricate polygon/mask annotation. Please provide examples or detailed descriptions of past projects. - Meticulous Attention to Detail: The difference between a correct and incorrect annotation in this project is subtle. You must have an exceptional eye for detail and a commitment to precision. - Ability to Master Technical Guidelines: You must be able to read, fully comprehend, and meticulously apply a complex, rule-based instruction document with numerous edge cases. - Excellent Visual Acuity: Experience working with grayscale, low-contrast, or scientific/medical imagery is essential. - Efficiency and Reliability: You are self-motivated, can manage your time effectively to meet deadlines, and understand workflows designed to improve efficiency (like the copy/paste/refine method described). - Native English Proficiency (US): Clear communication is key. This role is open to US-based native English speakers only. Highly Desirable (Brownie Points): - Experience with medical imaging (CT, MRI) or other forms of engineering/scientific imagery. - Familiarity with annotation platforms like V7 Darwin, Labelbox, or similar advanced tools. - A background or interest in engineering, physics, or a related technical field. Apply tot his job Apply To this Job