Role: Computer Vision Engineer / Sr Computer Vision Engineer
1. Work on identifying and implementing data pre-processing pipelines for various image datasets
2. Experimentation, Identifying, testing the right techniques / Deep Learning libraries to use to train models, and infer parts and degree of damage in the dataset (images of vehicles)
3. Training and deploying models for inferencing on cloud (and edge if required
4. Work on improving the accuracy of deployed models
Requirements
- Experience in state of the art deep learning, convolutional neural networks (ResNet50, Resnet101, Resnext101, Inceptionv3, Mobile-net)
- Hands on experience with (a) object detection (b) semantic segmentation (c) instance segmentation problems (incl. faster RCNN, SSD, Mask RCNN)
- Hands on experience with classical image processing techniques (feature engineering), using OpenCV, Pillow
- Proficiency in Python and OOPs concepts
- Proficient in building ML models on various deep learning and maching learning libraries using Pytorch, TensorFlow, Keras, sci-kit-learn, Numpy
- Familiar with training and deployment on cloud
- Experience with Pytorch essential
- Implemented research papers into production models
- Experience with command line Linux essential
- Startup experience preferred
