Amit Ray | Software Developer

Hi, I'm Amit Ray.

A

Self-driven, quick starter, passionate programmer with a curious mind who enjoys solving a complex and challenging real-world problems.

About

A Software Engineer currently working with Phonepe as an Android Developer. A passionate programmer and a team player with experience in writing test cases and performing unit tests for the software. An effective communicator who can work well with team members of different backgrounds to get work done on time. Proficient in Kotlin, Java, C and C++ and developing Android based apps. I have previously worked on designing mobile applications, web-based platforms and microcontrollers.

Languages: Kotlin, Java, C, C++, Python, HTML/CSS
Architecture: Clean Architecture, MVVM, MVP and MVC
Libraries: Retrofit, Co-routines, Material Design, Firebase, Glide, Timber, LeakCanary, Exoplayer
Jetpack Components: Jetpack Compose, Navigation Components, Room Database, Dagger-HIlt, WorkManager, Paging 3, Data Binding, CameraX
Tools & Technologies: Git, AWS, Figma, JIRA

Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.

Experience

Phonepe

Software Engineer

Worked on the QR scan optimisations for a better UPI experience.
Worked on Phonepe's ONDC-based e-commerce app Pincode. Added features like Recent Search, Referral, In-App Update and others.
In 4 months, developed a seller-side Android App based on the ONDC network for local stores with a team of 3 other engineers. Currently, it has 2 thousand Sellers onboarded.
Tools: Kotlin, Jetapck Compose, Navigation Component

June 2023 - Present | Bengluru, India

Broker Network

Software Engineer

Responsible for adding multiple features under Projects vertical (property listing and promotions) and revamping app to latest UI.
Added some significant features like PAN based KYC, Story Reels and News feed using Jetpack Compose, Paging 3 and Navigation Components.
Improved the response time by 20% by refactoring the codebase and changing database design and queries.
Added the document upload and downlod feaature as a generic component so it can be used in throughout the app
Tools: Kotlin, Jetapck Compose, Navigation Component

Sept 2022 - May 2023 | Mumbai, India

GetMega

Software Engineer

Customized a tree-based optimization algorithm that separates drugs into distinct groups to maximize the concurrent execution of drug dispenser robots; improved an optimization algorithm that reduced the cycle-time of the automation process by 25%.
Devised a customized recursion algorithm to extend the functionality of the current environment to a multi-robot and multi-system environment
Built a modular video analytics app using Flask, OpenCV that tracks the location of each human in a multi-camera environment; utilized perspective transformation, object detection, and object tracking to find the location of a human.
Increased the speed of the video analytics app by 20% by using a customized YOLOv3 algorithm to perform object detection and DeepSORT algorithm for multi-object tracking.
Tools: Python, Flask, OpenCV, Keras, Tensorflow, PyTorch

Nov 2021 - Aug 2022 | Bangalore, India

Trustt (Novopay Solutions)

Software Developer

Programmed a cloud-based web app using Flask and JavaScript aimed at storing, visualizing, and tracking temperature and humidity of each drug container to estimate the degradation of the drug.
Created an alert system to send notifications and emails when the parameters exceed the threshold.
Tools: Python, Flask, JavaScript

June 2019 - Nov 2021 | Bangalore, India

Yoofix Digital

Intern

Designed a library management system for a local library, where we undertook activities like requirement elicitation, preparing Data Flow and Entity-Relationship diagrams.
Delivered a solution for a POC involving Automatic Financial Document Classifier using Natural Language Processing and Support Vector Machines with 96% accuracy on the company’s data.
Tools: Python, Scikit-learn, NLTK

May 2018 - July 2018 | Yogyakarta, Indonesia

American University in Cairo (AUC)

Intern

Designed a library management system for a local library, where we undertook activities like requirement elicitation, preparing Data Flow and Entity-Relationship diagrams.
Delivered a solution for a POC involving Automatic Financial Document Classifier using Natural Language Processing and Support Vector Machines with 96% accuracy on the company’s data.
Tools: Python, Scikit-learn, NLTK

May 2016 - July 2016 | Cairo, Egypt

Projects

                
Music Player Web-App
                  A music streaming web app based on Django
                
AccomplishmentsTools: Django, HTML, CSS, Bootstrap, SQLite, AWS S3, Heroku
Register/login to the web app(with OAuth-based Google Sign-In).
Search and filter songs based on language and singer.
Create multiple playlists and add/remove songs to/from playlist.
Scroll through recently played/viewed songs.

Quiz Web-App
                  A quiz playing web app based on Django
                
AccomplishmentsTools: Django, HTML, CSS, Bootstrap, SQLite, Heroku
Register/login to the web app(with OAuth-based Google Sign-In).
Play Quiz and see the leaderboard

Blog Web-App
                  A simple and extensible blog web-app based on Flask.
                
AccomplishmentsTools: HTML, CSS, Bootstrap, Flask, SQLAlchemy, Postgresql, Python
Users can view posts and contact the admin via Contact Page.
Admin can Add, Delete, Update posts.

Visual Question Answering
                  An attention-based classification model that aims at generating an answer for a given input image.
                
AccomplishmentsIncorporated Convolution Neural Networks (CNN) for extracting image features and Long Short Term
                    Memory for extracting question
                    embeddings.
Tested the model on the COCO dataset, abstract scenes images, and got 69% overall accuracy on the
                    VQA evaluation metric.

Video Summarizer
                  A Seq2Seq model that generates a short summary of the given input video.
                
AccomplishmentsIncorporated CNN to detect and classify objects in the video frames and Long Short Term Memory for
                    generating a summary.
Evaluated the model on MSVD (Microsoft Video Description Corpus) dataset; achieved 0.77, 0.71,
                    0.52 scores respectively on ROGUE,
                    BLEU, METEOR evaluation metrics.

Image Generator
                  An image generator based on the concept of adversarial networks (GANs)
                
AccomplishmentsDeveloped system was tested on a human-face database and loss was calculated by comparing the PCAs
                    of generated and original image.
Calculated difference in PCA was less than 10%, depicting the successful generation of an image by
                    the generator.

Head Counting System
                  A system that calculates the attendance of the class from a panoramic image of a live classroom.
                
AccomplishmentsUsed Singular Value Decomposition for image compression; applied various image processing
                    techniques and morphological operations to
                    detect the number of heads.