Computer Vision Engineer

<p>Computer Vision Engineer — Data Labeling &amp; Annotation</p> <p><strong>Type:</strong> Temporary</p> <p><strong>Duration:</strong> 6 months - 12 months</p> <p><strong>What You'll Gain</strong></p> <ul> <li>Exposure to the full CV pipeline, from raw data to deployed model</li> <li>Mentorship from CV engineers working on production systems</li> <li>Hands-on experience with YOLO, PyTorch, and modern annotation workflows</li> <li>Concrete portfolio work — datasets, scripts, and model contributions — that translates directly to future ML/CV roles</li> </ul> <p><strong>What You'll Do</strong></p> <ul> <li>Annotate images and video for object detection (bounding boxes), segmentation (polygons/masks), and classification</li> <li>Help refine labeling schemas and class taxonomies as edge cases come up</li> <li>Write Python scripts to convert between annotation formats, validate label integrity, and generate dataset statistics</li> <li>QA labels and surface systematic errors or ambiguous cases</li> <li>Run baseline YOLO training experiments to evaluate dataset quality and identify labeling gaps</li> <li>Document conventions and edge-case decisions</li> </ul> <p><strong>Required</strong></p> <ul> <li>Recent graduate with a degree in CS, EE, AI/ML, or related field</li> <li>Working knowledge of Python and common CV libraries (NumPy, OpenCV)</li> <li>Attention to detail and patience for precision work</li> </ul> <p><strong>Nice to Have</strong></p> <ul> <li>Hands-on experience with YOLO</li> <li>Familiarity with PyTorch, segmentation masks, or model-assisted labeling workflows</li> </ul>