What are the responsibilities and job description for the Computer Vision Engineer position at BrightAI?
Computer Vision Intern — Data Labeling & Annotation
Type: Temporary
Duration: 6 months - 12 months
What You'll Gain
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
- 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 (NumPy, OpenCV)
- Attention to detail and patience for precision work
- Hands-on experience with YOLO
- Familiarity with PyTorch, segmentation masks, or model-assisted labeling workflows