Computer Vision Engineer

Computer Vision Intern — Data Labeling & Annotation Type: Internship / 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 Pursuing 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 #J-18808-Ljbffr BrightAI Corporation