Computer Vision Engineer

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

• Bachelors degree

  in Computer Science, Electrical Engineering, AI/ML, or related field
• Strong expertise in

  image processing

  techniques and algorithms
• Proven experience with

  CNNs

  and deep learning architectures (ResNet, YOLO, U-Net, etc)
• Proficiency in

  OpenCV

  for computer vision applications
• Hands-on experience with

  PyTorch

  for model development and training
• Strong Python programming skills
• Understanding of computer vision fundamentals (feature detection, image transforms, edge detection)

• Experience with object detection frameworks (YOLO, Faster R-CNN, SSD)
• Knowledge of semantic/instance segmentation techniques
• Familiarity with vision transformers (ViT, DETR, SAM)
• Experience with video processing and tracking algorithms
• Understanding of 3D vision, depth estimation, or SLAM
• Knowledge of model optimization (TensorRT, ONNX, quantization)
• Experience with GPU programming and CUDA
• Familiarity with cloud deployment and MLOps