Machine Learning Developer in Bengaluru, Karnataka, India

I developed a feature store in AWS Redshift that collates data from a number of different sources and makes them available in the desired format. It made the data clean, was always up-to-date, and ready to be used by machine learning models in production.

I improved an open-source data labeling tool in Django to create training data for an NLP classifier which was used in a chatbot. It enabled support for the dynamic options for every instance to be labeled.

I developed a machine learning model to show personalized ranking to users based on their historical and recent interaction with products as well as similarity with other users.

I worked on research projects on the economics of social networks in South India involving a randomized control trial.
I developed and customized a name-matching algorithm to match incoming patients to the project’s census data.

I developed an R-shiny-based machine learning application that predicts which Pokemon creature you would encounter at a given location and time in the Pokemon GO mobile game. The ML model was trained on a large publicly available dataset of the game.

I developed a real-time multiplayer game integrating Microsoft Kinect and Windows Phone that allows one player using the phone to generate obstacles for the player using the Kinect.

I made a deep learning based intent classification model for the chatbot of MakeMyTrip, the largest OTA in India. This intent classifier was based on the ULMFiT model. It is able to classify an intent among over a 100 classes.

I developed a joint model based on sequence to sequence (Seq2Seq) architecture which allows a user to extract the intent and slot values from an utterance given to a chatbot.

A Python-based app for classifying and parsing medical documents (including lab reports, prescriptions, vaccination certificates, etc.).

This makes the documents digitally available as well as searchable. This is very similar to what Google Photos does for unorganized photos. It makes all your medical documents organized in proper categories and easily searchable with the relevant medical terms, even if they are handwritten.