Computer Vision Intern, Palo Alto
Computer Vision Intern, Palo Alto
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Palo Alto 94306, USA
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Posted: less than a week ago
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Description
Computer Vision Intern
Palo Alto, California 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 rolesWhat 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 statisticsQA 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
Palo Alto, California 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 rolesWhat 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 statisticsQA 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
Highlights
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Company nameBrightAI
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Job positionComputer Vision Intern
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