Job Description:Work Actively as a part of the Computer Vision and Deep Learning Team to Train Computer
● Work Closely with the Data Sampling Team for Appropriate Dataset Collection
● Work on Challenging Problem Statements to fine-tune models with Huge Dataset
● Implementation of the SOTAArchitectures for Model Training.
What are we looking for
● Proficient with Training of Detection/Classification/Segmentation Models with Tensorflow/PyTorch
● Good understanding of Dataset Quality for Computer Vision Applications.
● Strong understanding of Model Training Dynamics. Should be able to find out the error and
resolve it based on training/eval metrics.
● Good Theoretical and Practical Knowledge with the fundamentals of Deep Learning, eg. CNNs,
Regularization Techniques, etc.
● Familiarity with State-of-the-Art Models like YOLO-series, Efficient Net/EfficientDet, etc.
● Experience with using Docker containers for Computer Vision/Deep Learning