Deep Learning Engineer at Nanonets

Ideal candidate should have the following skillset

1) Python

2) Tensorflow

3) Experience building and deploying systems

4) Experience with Theano/Torch/Caffe/Keras all useful

5) Experience Data warehousing/storage/management would be a plus

6) Experience writing production software would be a plus

7) Ideal candidate should have developed their own DL architechtures apart from using open source architechtures.

8) Ideal candidate would have extensive experience with computer vision applications

Candidates would be responsible for building Deep Learning models to solve specific problems. Workflow would look as follows:

1) Define Problem Statement (input -> output)

2) Preprocess Data

3) Build DL model

4) Test on different datasets using Transfer Learning

5) Parameter Tuning

6) Deployment to production