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Recrutez un Computer Vision Engineer
Engineers specialized in image and video analysis, object detection, and visual recognition systems. They build solutions for quality inspection, autonomous systems, and visual data processing.
D\u00e8s $12-18/hrMise en relation sous 48hProfessionnels v\u00e9rifi\u00e9s
Comp\u00e9tences cl\u00e9s
Chaque Computer Vision Engineer sur la plateforme AI10 est v\u00e9rifi\u00e9 pour ces comp\u00e9tences essentielles.
Image Classification & Detection
OpenCV & Deep Learning
Edge Deployment & Optimization
Video Analytics & Tracking
Tarification
Tarification transparente et abordable pour les meilleurs talents IA.
\u00c0 partir de
$12-18/hr
- Professionnels v\u00e9rifi\u00e9s et test\u00e9s
- Horaire flexible ou par projet
- Mise en relation sous 48 heures
- Gestion de projet d\u00e9di\u00e9e
- Garantie de remplacement
FAQ
Questions fréquemment posées
What computer vision systems can your engineers build?
Our CV Engineers build object detection, image classification, semantic segmentation, pose estimation, OCR, facial recognition, and anomaly detection systems. They work with both 2D imagery and 3D point clouds for industrial and consumer applications.
Can computer vision work with existing camera systems?
Yes. Our engineers optimize models for your existing cameras and infrastructure — IP cameras, industrial vision sensors, mobile devices, or drones. They handle resolution, lighting, and angle variations that affect real-world performance.
How much training data is needed for computer vision?
It depends on complexity. Simple classification needs 500-1,000 images per class. Object detection needs 1,000-5,000 annotated images. Our engineers use transfer learning, data augmentation, and synthetic data generation to work effectively with smaller datasets.
Can models run on edge devices?
Yes. Our CV Engineers optimize models for edge deployment using quantization, pruning, and architecture search. They deploy on NVIDIA Jetson, Intel NCS, mobile devices, and custom hardware — achieving real-time inference at the point of capture.