Work Actively as a part of the Computer Vision and Deep Learning Team to Train Computer Vision Models
Work closely with the Data Sampling Team for Appropriate Dataset Collection
Work on Challenging Problem Statements to fine-tune models with a Huge Dataset
Implementation of the SOTA Architectures for Model Training

What Are We Looking For

Proven work experience of 2-4 years.
Proficient in 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 of the fundamentals of Deep Learning, e.g. 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.

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