May 2024 – Oct 2024 · 5 mos · On-site

• Worked as Back-End Engineer in the Finance Pod , leveraging Django,Postgre-SQL,Docker, and Google Cloud Platform (GCP) for building API, project tasks and infrastructure and inventory management.
• Designed and developed an API for migrating from SendGrid to Hedwig SDK service, scaling message/email capacity from 100K to 2 million. Ensured unique identifiers for each email, extended support for attachments and images, and utilized hash-coded links with Google Cloud to automate data fetching, improving efficiency by 15%.
• Reengineered the invoicing logic across the platform to ensure uniformity and accuracy for all customers company-wide, enabling the number of invoices to be managed to increase up to 10 billion per customer.
• Implemented the Factory Design Pattern to streamline and modularize the codebase for the Pay App and General Invoice modules in the Finance Department.
• Developed advanced sorting logic for customer records, increasing field query performance by 70%. Enhanced the admin panel backend by adding comprehensive filters and new sorting fields for improved user experience.

Jan 2024 – May 2024 · 4 mos · On-site

• Built and deployed a chat-bot for PDFs and Excel sheets uploaded by users on the BEAM website, utilizing Django, Fast-API, RAG Langchain Architecture and Fine Tuned Large Language Models (GenAI). Employed MongoDB and Google Cloud as the database and used Kubernetes and Docker for containerization. Additionally, utilized Fast API to deploy the BEAMGPT application on the BEAM website which was further extended to Accelerate website due to its high efficiency.
• Automated the customer catalog to invoice generation process on the Accelerate website, leveraging data science expertise
• to assess project feasibility and build the ML model from scratch. Achieved an accuracy exceeding 77% through rigorous
• evaluation and comparison of several models. Integrated the solution using Kafka, Celery, and FastAPI.

Sep 2022 – Mar 2024 · 1 yr 6 mos · Remote

• Actively mentored and supported over 400 students, providing guidance and resolving project-related and Data Structures
• Algorithms (DSA) in Java, Spring and Spring Boot .

Aug 2022 – Aug 2023 · 1 yr · IIITA · On-site

May 2022 – Jun 2022 · 1 mo

• Worked on a Flask-based web application that leverages OpenCV for real-time face recognition to automate attendance
• tracking reducing manual entry time by 60%.
• Developed a unique algorithm using K-Nearest Neighbors (KNN) machine learning model for face identification with an
• accuracy of 95%.
• Enhanced user management system by implementing functionalities for adding, listing, and deleting users; incorporated
• Docker for containerized deployment, reducing deployment time by 50% and improving scalability by 40%.

Aug 2021 – Jun 2022 · 10 mos · On-site

Jan 2021 – Dec 2021 · 11 mos · IIITA · On-site

Jan 2021 – Mar 2021 · 2 mos · Remote · Remote

• Acquired comprehensive knowledge and hands-on experience with various machine learning technologies and algorithms, in-
• cluding Linear Regression, Logistic Regression, Decision Tree Regression, Random Forest Regression, and Natural Language
• Processing (NLP). Utilized these skills to tackle real-world data analysis challenges and make data-driven decisions.
• Successfully improved the performance of a restaurant review categorization model, enhancing its accuracy to 76%. This
• achievement involved fine-tuning various machine learning algorithms and data preprocessing techniques to drive actionable
• insights.