Headline

Software Developer | Data-Driven Applications | Python • Django • React | AI/ML & Analytics Enthusiast

About

I am a Software Developer and Data Analytics enthusiast and a recent graduate in Electrical and Electronics Engineering from M S Ramaiah Institute of Technology. I enjoy building scalable applications and solving real-world problems through technology across mobile, web, and backend systems. I recently worked as a Development Intern at Perfios, where I contributed to building a Remote Property Verification platform integrating Flutter mobile applications, React/TypeScript web portals, and Django REST backend services. My work included implementing AR-based property measurement using ARCore and ARKit, developing real-time dashboards using WebSockets with Django Channels, and designing backend services for geolocation verification and document workflows using MongoDB. Previously, I worked on machine learning and NLP projects during internships at Code Clause and Navodita Infotech, including a Parkinson’s disease prediction system and sentiment analysis on IMDB movie reviews, improving model performance through data preprocessing and feature engineering. I hold certifications in Data Analytics Essentials and Introduction to Data Science by Cisco, and Introduction to MongoDB by MongoDB. My interests include full stack development, backend engineering, real-time systems, and data-driven applications. I am currently seeking opportunities where I can contribute to building scalable software products and impactful technology solutions.

Location

Bengaluru

AI stack

aistudio

langchain

ollama

openai

Work experience

Developer Intern at Perfios, Oct 2025 - Jun 2026 · 9 mos, Bengaluru, I worked as a Development Intern at Perfios, where I contributed to building a Remote Property Verification platform that digitizes property inspection workflows. I developed cross-platform mobile features in Flutter, including AR-based property measurement using ARCore/ARKit to enable accurate remote dimension verification. On the backend, I designed scalable services using Django REST, implementing geolocation validation, secure document workflows, and automated notification systems. I also built a real-time admin dashboard using React, TypeScript, and WebSockets to monitor verification status, document uploads, and application lifecycle events with low-latency updates. My work focused on building reliable full-stack systems that integrate mobile, web, and backend infrastructure to support secure and scalable digital verification processes.

AI Intern at Fraction Labs, Feb 2025 - May 2025 · 4 mos, During my internship at Fraction Labs, I gained hands-on experience in AI and data engineering, working extensively with tools such as Apache Airflow, Crew AI, AutoGPT, and LangChain. I explored key concepts in Large Language Models (LLMs), Generative AI, and AI Agents, which helped me build a strong foundation in prompt engineering and agent-based workflows. Throughout the internship, I contributed to several real-world projects, including the development of a customer triage system for automating support workflows, a personalized content recommendation engine, and AI-driven tools for content writing such as blog and article generation. I also worked on creative generative AI applications like a synthetic deep-sea image generator and a poster generator for companies to streamline marketing content creation. This experience provided me with practical exposure to integrating advanced AI tools into scalable systems and deepened my understanding of the AI product development lifecycle.

Data Science Intern at CodeClause, Nov 2024 - Dec 2024 · 2 mos, Hybrid, Parkinson's Disease Prediction UI Data Preprocessing: Implemented various preprocessing techniques, including normalization of data and addressing class imbalance by applying oversampling methods, which led to a 12% improvement in model accuracy. Model Training & Optimization: Utilized machine learning algorithms to train predictive models, continuously refining them to improve performance and ensure accurate predictions. UI Development: Developed the user interface, allowing seamless input of medical data and displaying results clearly for end-users, making the tool accessible to both medical professionals and patients. Performance Evaluation: Evaluated the model's performance using standard metrics, and optimized the models to reduce prediction errors, making the tool more reliable for real-world applications.

Data Analytics Intern at Navodita Infotech, Oct 2024 - Nov 2024 · 2 mos, Hybrid, Sentiment Analysis on IMDB Movie Reviews Data Preprocessing: Cleaned and preprocessed large sets of unstructured text data, including tokenization, stopword removal, and lemmatization, to prepare it for model training. Model Training & Optimization: Worked with machine learning algorithms, including Logistic Regression and Random Forest, and used techniques like hyperparameter tuning to improve model performance. Accuracy Improvement: Increased sentiment analysis accuracy by 10% by refining data preprocessing techniques (e.g., stemming, TF-IDF vectorization) and optimizing NLP models. Data Visualization: Used Matplotlib and Seaborn to visualize sentiment trends over time, providing actionable insights that supported brand management and marketing decisions. Sentiment Trends Reporting: Presented detailed reports and dashboards to stakeholders, showing sentiment patterns for movies and their impact on the brand reputation. Collaboration: Worked closely with team members to iterate on models and collaborate on refining data preprocessing pipelines.

Education

Bachelor of Engineering - BE, Electrical and Electronics Engineering, Ramaiah Institute Of Technology