Role Overview
Develop and deploy computer vision solutions using deep learning, image processing, and modern CV frameworks. Build production-ready systems for visual understanding and analysis.
Responsibilities
- Design and implement computer vision models for object detection, segmentation, and classification
- Develop image processing pipelines for enhancement, filtering, and feature extraction
- Build and optimize CNN architectures for various computer vision tasks
- Implement CV solutions using OpenCV for real-time image and video processing
- Train and fine-tune deep learning models using PyTorch for production deployment
- Optimize models for performance, accuracy, and inference speed
- Collaborate with cross-functional teams to integrate CV solutions into products
Requirements
Bachelor's degree in Computer Science, Electrical Engineering, AI / ML, or related fieldStrong expertise in image processing techniques and algorithmsProven experience with CNNs and deep learning architectures (ResNet, YOLO, U-Net, etc.)Proficiency in OpenCV for computer vision applicationsHands-on experience with PyTorch for model development and trainingStrong Python programming skillsUnderstanding of computer vision fundamentals (feature detection, image transforms, edge detection)Preferred
Experience with object detection frameworks (YOLO, Faster R-CNN, SSD)Knowledge of semantic / instance segmentation techniquesFamiliarity with vision transformers (ViT, DETR, SAM)Experience with video processing and tracking algorithmsUnderstanding of 3D vision, depth estimation, or SLAMKnowledge of model optimization (TensorRT, ONNX, quantization)Experience with GPU programming and CUDAFamiliarity with cloud deployment and MLOps