INTERNSHIP DETAILS

Computer Vision Intern

CompanyBrightAI Corporation
LocationPalo Alto
Work ModeOn Site
PostedMay 20, 2026
Internship Information
Core Responsibilities
The intern will annotate images and videos for object detection and segmentation while refining labeling schemas. They will also write Python scripts for data validation and run baseline YOLO experiments to evaluate dataset quality.
Internship Type
full time
Company Size
131
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
BrightAI is transforming essential services with Physical AI—real-world intelligence that drives proactive, data-driven operations. Built on the Stateful platform, BrightAI empowers operators of critical infrastructure to collect and connect sensor data in real time, uncover hidden insights, and make smarter decisions. From predictive diagnostics and autonomous robotics to digital twins and AI-enabled workflows, BrightAI solutions serve industries including water, power, gas compression, pest control, HVAC, and manufacturing. By turning complex physical signals into actionable intelligence, BrightAI is redefining how essential services are delivered and sustained.
About the Role

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
Key Skills
Computer VisionData LabelingPythonYOLOPyTorchNumPyOpenCVObject DetectionImage SegmentationClassification
Categories
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Computer Vision Intern - InternshipsHQ