Algorithm Developer

The job involves building, training, and testing multiple Convolutional Neural Network (CNN) models, optimizing model training and inference using multiple GPUs and CPU cores. The ideal candidate should have a keen interest in Life Sciences, Image processing, Genomics, and Multi-omics analysis, and should be interested in reading and implementing research papers in the relevant field. The candidate should possess strong experience with Deep Learning frameworks such as TensorFlow, Keras, and PyTorch, as well as strong programming skills in Python and experience with libraries like Scikit-Learn and NumPy. Experience in training Object detection Models like YOLOv3/Mask CNN and semantic segmentation models like DeepLab, Unet, along with a good understanding of image processing and computer vision algorithms like watershed and histogram matching is required. Experience in cell segmentation and membrane segmentation using CNNs is optional. Minimum qualification required is B.E/B.Tech. in Computer Science or equivalent stream. The candidate must have experience with image processing, 2-10 years of experience, good Python programming and algorithmic skills, experience with deep learning model training using any known framework, and working knowledge of genomics data in R&D. Preferred qualifications include understanding of one or more omics data types (transcriptomics, metabolomics, proteomics, genomics, epigenomics), and prior work experience as a data scientist, bioinformatician, or computational biologist will be a big plus. This is an individual contributor role with a CTC ranging from 15-40 LPA. The key skills required for this position are Image Processing, PyTorch, and TensorFlow.,