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Latin AmericaFactored was conceived in Palo Alto, California by Andrew Ng and a team of highly experienced AI researchers, educators, and engineers to help address the significant shortage of qualified AI & Machine-Learning engineers globally. We know that exceptional technical aptitude, intelligence, communication skills, and passion are equally distributed around the world, and we are very committed to testing, vetting, and nurturing the most talented engineers for our program and on behalf of our clients. We are seeking a highly skilled Machine Learning Engineer with expertise in computer vision to design, develop, and optimize deep learning models for image-related tasks. Responsibilities Develop and fine-tune models for image classification, object detection, segmentation, and generative modeling using TensorFlow, PyTorch, or Keras. Implement techniques such as resizing, normalization, data augmentation, and feature extraction to improve model performance. Optimize and deploy computer vision models on cloud platforms (AWS, GCP, Azure), edge devices, and specialized hardware (GPUs, TPUs). Use CI/CD, model versioning, and monitoring tools to ensure reliable and scalable deployment of vision models. Improve model speed and performance using quantization, pruning, and hardware acceleration techniques. Qualifications Strong Python programming skills with proficiency in deep learning frameworks (TensorFlow, PyTorch, or Keras). Expertise in designing, training, and fine-tuning models for image classification (ResNet, EfficientNet), object detection (Faster R-CNN, YOLO, SSD), and image segmentation (U-Net, Mask R-CNN). Strong understanding of image preprocessing techniques (resizing, normalization, data augmentation). Experience with computer vision libraries such as OpenCV and torchvision. Experience with transfer learning and adapting pre-trained models. Ability to deploy models on cloud platforms (AWS, GCP, Azure) and specialized hardware (GPUs, TPUs). Familiarity with MLOps tools for automating ML pipelines. #J-18808-Ljbffr
