CureBay

We are looking for a highly motivated Deep Learning Engineer with strong expertise in computer vision and audio analysis. The ideal candidate should be comfortable working with CNNs, pretrained models, attention mechanisms, vision transformers, video processing, object detection, and audio classification. You will be part of a team developing AI-driven solutions using multi-modal deep learning. Responsibilities Design and implement deep learning models for image, video, object detection, and audio classification tasks. Apply and fine-tune CNN-based architectures and Vision Transformers (e. g., ViT, Swin). Integrate attention mechanisms (e. g., SE, CBAM, Transformer attention) into model architectures for enhanced feature learning. Utilize pretrained models for transfer learning and multi-task learning. Work with video data using spatiotemporal modeling techniques (e. g., 3D CNNs, temporal attention). Extract and process features from audio using spectrograms, MFCCs, or learned embeddings. Evaluate and optimize models for speed, accuracy, and robustness. Collaborate across teams to deploy models into production. Requirements Strong programming skills in Python, with experience in PyTorch or TensorFlow. Hands-on experience with CNNs, pretrained networks, and attention modules. Solid knowledge of Vision Transformers, including recent architectures (e. g., Swin, DeiT). Understanding of attention mechanisms (self-attention, cross-attention, squeeze-and-excitation, etc. ). Experience implementing and training object detection models (YOLO, SSD, Faster R-CNN, RetinaNet, DETR). Experience in video analysis and temporal modeling. Strong grasp of audio classification workflows and features. Experience handling large-scale datasets and designing data pipelines. Familiarity with training strategies for deep models, including learning rate scheduling, early stopping, and data augmentation. This job was posted by Anshika Mahapatra from CureBay.

We are seeking a highly motivated Deep Learning Engineer with specialized expertise in computer vision and audio analysis. As a part of our team developing AI-driven solutions utilizing multi-modal deep learning, you will play a crucial role in designing and implementing deep learning models for various tasks such as image, video, object detection, and audio classification. Your responsibilities will include integrating attention mechanisms into model architectures, utilizing pretrained models for transfer learning, and working with video data using spatiotemporal modeling techniques. Additionally, you will be responsible for extracting and processing features from audio and evaluating and optimizing models for speed, accuracy, and robustness. Collaboration across teams to deploy models into production will also be a key aspect of this role. The ideal candidate should have strong programming skills in Python, proficiency in PyTorch or TensorFlow, and hands-on experience with CNNs, pretrained networks, and attention modules. A solid understanding of Vision Transformers, recent architectures, and attention mechanisms is essential. Experience in implementing and training object detection models, video analysis, temporal modeling, and audio classification workflows is highly desired. Moreover, familiarity with handling large-scale datasets, designing data pipelines, and training strategies for deep models will be beneficial for this position. If you are passionate about deep learning, possess the required skills and experience, and are eager to contribute to cutting-edge AI solutions, we encourage you to apply for this position. Join us at CureBay and be a part of our dynamic team dedicated to pushing the boundaries of technology and innovation.,

The ideal candidate will be responsible for providing care to patients while adhering to compliance standards. This candidate should be able to recognize patient needs and prioritize those needs with the advice outlined by physicians. Responsibilities Assure quality care by adhering to standards set by the physicians Provide care education to patients in person or over the phone Adhere to compliance guidelines throughout processes Qualifications Must be a Registered Professional Nurse with current licensure BSc nursing (with training experience) GNM/ANM