Software Engineer MERN, Flutter, Machine Learning

RUSHIKESH MUSALE

California ***************@*****.*** +1-951-***-**** Linkedin

TECHNICAL SKILLS

Languages - JavaScript, Python, C, Dart, SQL, HTML, CSS Frameworks and Tools - Node.js, Express.js, React.js, Redux, Flutter, Flask, Angular, RESTful APIs, GraphQL, XML, Jest, React Testing Library, TensorFlow, Keras, PySpark.

Database - MySQL, MongoDB, Firebase, NoSQL

Tools and Technology - Amazon Web Services (AWS), Docker, Git, GitHub, Agile, Scrum, JIRA, SDLC, Postman, Data Structures and Algorithms

WORK EXPERIENCE

Software Developer Intern (Flutter, Dart, Node.js, Express.js, MongoDB, NoSQL, Git) New York, USA Superstars Inc. Sept 2023 – Feb 2024

● Redeveloped a video-centric professional networking Android/IOS app amplifying recruiter-candidate interaction through detailed video profiles.

● Led the design and implementation of critical app features like authentication, user profile, posts, stories, video resume, recommendations and recruiter portal using Bloc design pattern.

● Engineered a robust API in Express and Node.js, enabling seamless data retrieval from NoSQL database, leading to a 25% decrease in front-end loading time, achieving 200ms average response time and improved user experience.

● Implemented authentication and authorization mechanisms using JSON Web Tokens (JWT) and OAuth2, handling thousands of requests daily.

● Designed and optimized MongoDB database capable of storing up to 1 terabyte of data, enhancing system performance, scalability, and data integrity. Optimized MongoDB queries and implemented effective indexing strategies, resulting in a 30% improvement in database performance and reduced latency.

● Enhanced app security by implementing two-factor authentication and encryption protocols reducing the risk of security breaches by 20%, fortifying user data integrity for a secure professional networking experience.

● Utilized GitLab for version control, issue tracking, and collaborative software development, ensuring seamless coordination and efficient code management throughout the project lifecycle. PROJECTS

Carbon Footprint Tracker (React.js, Python, Flask, MongoDB, Tensorflow, Keras, Deep Learning)

● Created a web application using Python, Flask and React.js, built on a microservices architecture that facilitates information exchange through REST APIs between the user and the hosted back-end system.

● Developed and trained two distinct image classification models: one built from scratch using a custom convolutional neural network (CNN) and another leveraging transfer learning with a pre-trained ResNet-50 model, recognizing over 50+ objects to assess their carbon emissions.

● Created extensive research based Algorithm to calculate user’s monthly carbon emissions based on input data. Geo-Spatial Traffic Dynamics Analysis (Node.js, React.js, Express.js, MongoDB, Python, PySpark, Leaflet, RestAPI)

● Leveraged PySpark to efficiently process and analyze 5.76 GB of US spatial-temporal data, performing filtering, aggregation, and partitioning on road construction and accident datasets for analysis.

● Conducted a detailed analysis to identify correlations between road construction activities and increased accident rates, utilizing cluster analysis to detect accident hotspots and time series analysis to uncover temporal patterns, which were then visualized on an interactive US map within the React.js web application. BeSocial (Flutter, Dart, Node.js, Express.js, MySQL, AWS S3, Docker, Python, keras, Natural language Processing)

● Engineered a full-stack social media app, integrated AWS S3 for scalable, secure media storage, and containerized with Docker to ensure efficient content handling, consistent environments, and streamlined deployments.

● Developed a self-learning customer service chatbot using TensorFlow and Keras, implementing a sequence-to-sequence

(Seq2Seq) model with LSTM layers for dynamic conversation handling. Integrated with the app using Node.js and MySQL. Early Detection of Alzheimer's (Python, Flutter, Dart, Tensorflow, Keras, Firebase)

● Innovatively gamified Cantab tests within a Flutter application for remote admission and ensured adherence to testing protocols. Employed a linear regression and k-means clustering models and integrated with Firebase to accurately assess and generate personalized risk scores for early detection of Alzheimer's disease. EDUCATION

University of California, Riverside Riverside, CA

Masters in Computer Science Sept 2022 - Dec 2023

University of Mumbai Navi Mumbai, India

Bachelor of Engineering in Computer Engineering Aug 2018 - May 2022

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