Front-End Developer, Full stack Developer

JAYASUDHA KALAMEGAM

+1-206-***-**** Redmond, WA *********.*********@*******.*** LinkedIn Portfolio SUMMARY

• Experienced Front-End Developer with 5+ years of proven success building modern, responsive, and dynamic web applications and Single Page Applications (SPAs) using React, JavaScript, HTML5, CSS3, and AJAX.

• Strong ability to effectively translate UI/UX designs into functional, high-performing, and visually appealing user interfaces. Focused on delivering intuitive, scalable, and cross-platform web solutions. EDUCATION

City University of Seattle (Jul 2023 - Mar 2025)

Master of Science in Computer Science (President’s Honors) GPA: 4.00 Anna University, Chennai, India (Jun 2012 - Apr 2016) Bachelor of Engineering in Computer Science CGPA: 7.9/10 TECHNICAL SKILLS

Programming Languages JavaScript, TypeScript, Java, Python, Shell Scripting Databases MySQL, SQL, MongoDB

Web Technologies HTML5, CSS3, jQuery, AJAX, React, React Native, Node.js, Flask Development and Testing Tools Git, Visual Studio, Postman, Docker, TeamCity, UDeploy, AutoSys Machine Learning and AI LLM, RAG, CNN, PyTorch, TensorFlow, Scikit-learn, Keras Cloud Services and Deployment AWS (EC2, SageMaker, S3, Lex, Lambda, VPC, Amazon Rekognition), Azure CERTIFICATIONS

AWS Cloud Practitioner, Career Essentials in Generative AI - Microsoft & LinkedIn WORK EXPERIENCE

TATA Consultancy Services, Chennai, India – Associate Software Engineer (Apr 2019 - Jun 2022)

• Collaborated with cross-functional teams to translate banking requirements into system-level solutions, enhanc- ing data management processes and significantly improving the efficiency of large-scale distributed systems

• Developed a custom tool to visualize AutoSys job dependencies and optimize scheduling, reducing resource conflicts and execution delays, and improving overall job efficiency by 25% (JavaScript, AutoSys, Shell Scripting) TATA Consultancy Services, Chennai, India – Application Developer (Feb 2017 - Mar 2019)

• Led the development of a distributed, real-time data processing system for a global banking client, improving operational efficiency by 40% and ensuring high availability and fault tolerance in financial systems

• Engineered secure, scalable transmission modules using NDM SFTP for handling large volumes of financial data, incorporating advanced exception handling and performance optimizations to meet banking industry standards PROJECTS

Personal Smart Finance

• Created an AI-powered financial chatbot using Retrieval-Augmented Generation (RAG), FAISS, and LLM, improving financial tip accuracy by 85% through embedding-based similarity search with all-MiniLM-L6-v2

• Designed and built a full-stack expense tracker using the MERN stack, enabling users to track and categorize expenses 30% faster, with real-time data visualization and intuitive interface powered by Vite and Tailwind CSS React Native Weather Application

• Built a cross-platform React Native app using Expo, delivering real-time weather forecasts, sunrise/sunset times, humidity, and UV index with animated GIF backgrounds and interactive UI for enhanced user engagement Drowsy Driver Detection using Python

• Constructed and trained a Convolutional Neural Network (CNN) to analyze 726 eye images, enhancing real-time detection of drowsiness indicators like eye closure while driving; applied data augmentation techniques to boost accuracy by 35%, especially for individuals wearing glasses, ensuring robust performance across conditions Home Run Derby Projection Model

• Developed a MERN stack application to predict MLB Home Run Derby outcomes using sabermetrics, achieving 90% accuracy, and deployed it on Azure with a user-friendly interface for player comparisons and results

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