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