Souranil Sen_

Software Engineer, Unity Technologies

[email protected]
San Francisco, California


I am currently working as a Software Engineer at Unity Technologies as part of the Unity Platform team. I code in Python and Go at work building micro-services at scale, but also do other languages whenever required. I graduated from Stony Brook University with a Masters in Computer Science.I did my research on Computer Vision under the guidance of Prof. Roy Shilkrot @The Human Interaction Lab. I am also interested in IoT Computer Networks, and have worked on the same for scaling IoT Pub/Sub Networks, here's a paper which I worked on last summer - A Highly Resilient and Scalable Broker architecture for IoT applications which was published in COMSNET 2018. I also have quite some experience as a Full Stack Developer and I generally work on backend technologies as well as love automation.

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I am an outgoing Software Engineer seeking Full Time Opportunities to leverage my technical and professional expertise. I have worked as a Full Stack Developer in Quintype & ThoughtWorks in the few years and have helped build scalable platforms for different products. At Quintype I have been working on a SaaS solution for Publishers which helped them get online at scale without the pain of building everything on their own. I was part of the team responsible for the core product and I invested my time working on different fascets from scalable APIs to Analytics, where I solved critical problems such as handling millions of users which involved huge amounts of read and write operations to various caching solutions. I was also part of handling one of the customer BloombergQuint which consume our APIs for their publishing solutions and helped them build the backend & front-end components necessary for the same. I was also part of building Ruby gems & Node.js modules for our core APIs to be consumed seamlessly. I am looking forward to challenging full time opportunities.


Stony Brook University

2017 - 2018

Masters in Computer Science

GPA - 3.88


  • - Computer Vision
  • - Analysis of Algorithms
  • - Machine Learning
  • - Fundamentals of Computer Networks
  • - HCI
  • - Network Security
  • - Visualization
  • - Theory of Database Systems


Unity Technologies

2018 - Present

Software Engineer

  • Working with Go on building micro-services;

Stony Brook University

2017 - 2018

Graduate Assistant

  • Worked on a digital Mind Map for Schizophrenia patients with Prof. Rong Zhao, which includes building clusters of meaningful memories from their digital media, reinforced by data provided by family members (Python, TensorFlow);
  • Designed and implemented APIs for a multi-tenant conference app (NYSTAR) & an app made in React Native (Node.js, SQL);
  • Proposed and automated the deployments at CEWIT (Docker, docker-compose, shell, Jenkins, Gitlab);
  • Achievements: Received appreciation for driving nystar to release and automating the CI/CD pipeline;

Quintype Inc.

2016 - 2017

Full Stack Engineer

  • Worked on re-designing the product from a monolith to micro-services(Clojure);
  • Backend development on the data team for importing RSS feeds to the publishing platform;
  • Building a real-time stock data streaming service (RxJS, websockets) using the observer pattern (Node.js);
  • Awards: Received appreciation on effectively mitigating production issues on call and leading a team;


2014 - 2015

Software Consultant

  • Worked on developing backend data driven services for an enterprise application RedE (Ruby, PostgreSQL);
  • Refactored the core transition code using state machines to be more modular and flexible to changes;
  • Developed dashboards for live data visualizations (D3.js); Migrated & Automated deployment using AWS OpsWorks;

TCS Innovations Labs

2013 - 2014

Solutions Developer

  • Worked on an Enterprise Social Networking Platform as a part of the Re-imagination of Workplaces Initiative (Java, Ruby, PostgreSQL, ElasticSearch);


java 80%

python 60%

JavaScript(Node.js, React/Redux) 90%

SQL 70%

Scikit-Learn 50%

NumPy 50%

OpenCV 70%

TensorFlow 50%

Docker 70%

Kubernetes 60%

MongoDB 50%

Git 90%

My projects_


Dark Patterns Detection for increased Web UI Neutrality (CSE 523/524)

This is a project I am working on at the Human Interaction Lab @Stony Brook University under the guidance of Prof. Roy Shilkrot. The primary idea is to detect certain dark patterns which may/maynot be able to skew user opinion as well as influence user actions by using different types of design techniques. This is being used almost everywhere and in almost all most heavily used websites. Our goal in this project is the detection of such dark patters for websites and show it to users for more awareness. Here's a glimpse of the existing dark patterns - Dark Patterns Hall of Shame

Used stack:

  • Python
  • TensorFlow
  • Javascript
  • Deep Learning

DeepVO - Visual Odometry with Deep Recurrent Convolutional Neural Networks - CSE 527

Deep Learning approach for Monocular Visual Odometry using Deep Learning; Inspired from the paper DeepVO.

Used stack:

  • LSTM
  • CNN
  • TensorFlow
  • Python
  • OpenCV

3D Fabricated Arm Band with Workout detection

3D printed an arm band for a raspberry pi with a gyroscope connected. Used DTW to detect quality of workouts based on the data from the sensors and send user feedback using an iOS app. Won the Most Innovate Idea Award at [email protected]

Project Report

Used stack:

  • Raspberry Pi
  • Python
  • Machine Learning
  • 3D fabrication
  • HCI


Developed an online real-time one-to-one tutoring platform to empower students for on-demand learning.

Used stack:

  • Node.js
  • PostgreSQL
  • Angular.js
  • Websockets


As a part of the Quintype Platform, helped build the BloombergQuint app consuming the Quintype API. This was part of my stint at Quintype. This is primarily built using Ruby on Rails and the quintype-ruby gem that helps integrate with the Quintype Platform.


Used stack:

  • Ruby on Rails
  • Node.js
  • Liquid.js
  • websockets
  • Clojure

NYC Traffic Accident Data Analysis

Analyzed and visualized NYPD Motor Vehicle Collision dataset for accidents in New York City(1 Million rows). Used stratified sampling using K-means for data reduction and Principal Component Analysis(PCA) for dimension reduction. MongoDB was used for storing data, D3 and deck.gl(WebGL) were used for creating visualizations

Used stack:

  • Python
  • NumPY
  • Scikit-Learn
  • React.js
  • D3
  • WebGL
  • deck.gl

Get in touch_