Computer Vision Engineer

Computer Vision Intern — Data Labeling & Annotation

Type: Internship / Temporary

Duration: 6 months - 12 months

• 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

• 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

• Pursuing a degree in CS, EE, AI/ML, or related field
• Working knowledge of Python and common CV libraries (Num Py, OpenCV)
• Attention to detail and patience for precision work

• Hands‑on experience with YOLO
• Familiarity with PyTorch, segmentation masks, or model‑assisted labeling workflows