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Software Engineer with less than a year in Machine Learning & AI
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Assessing your cultural and operational fit
B.Tech graduate in Electronics and Computer Engineering with hands-on experience in machine learning, deep learning, computer vision, data engineering, and generative AI. Skilled in Python, SQL, PySpark, Databricks, TensorFlow, and Scikit-learn, with experience building AI and data-driven systems through projects and internship experience.
REVA University
Bachelor of Technology (B.Tech) · Electronics and Computer Engineering
August 1, 2022 – June 30, 2026
Capgemini
Software Engineering Intern (IICS)
April 1, 2026 – June 30, 2026
India
Pathological Voice Classification using Hybrid CNN-BiLSTM
June 23, 2026 – Present
Developed a deep learning model to classify pathological and healthy voice samples using the PhysioNet VOICED dataset, leveraging CQCC, CFCC, and MFCC acoustic features with clinical metadata. Designed and evaluated hybrid CNN-BiLSTM architectures with data augmentation and 5-fold cross-validation, achieving 87.27% accuracy and 0.939 AUC using CQCC features.
View ProjectIoT & ML: Traffic Signal Optimization
June 23, 2026 – Present
Developed an IoT + ML system optimizing traffic flow through real-time computer vision using Raspberry Pi and Flask for live data capture and cloud processing. Trained ML model on dynamic traffic datasets to predict flow and automatically adjust signal timing, reducing congestion via adaptive control through Flask API and hardware integration.
View ProjectAgentic AI: Multilingual Loan Advisory Chatbot
June 23, 2026 – Present
Built a multilingual chatbot integrating Sarvam AI for translation and OpenAI GPT for personalized financial advice with RAG-based contextual response generation. Generated personalized loan recommendations from user data, improving accuracy and multilingual support.
View ProjectDockerized Data Pipeline with Dagster
June 23, 2026 – Present
Built a containerized ETL pipeline using Docker and Dagster to fetch real-time stock data from Alpha Vantage API, implementing rate limiting, retry logic, and validation for fault-tolerant processing with PostgreSQL UPSERT persistence. Designed a scalable dual-mode architecture (Dagster + standalone), monitored via Dagster UI and visualized through a Streamlit dashboard with charts and insights.
View ProjectGoogle Cloud Computing Foundations Certificate
Google Cloud
June 1, 2026 – Present
Networking Basics
Cisco
June 1, 2026 – Present
AI For Everyone
DeepLearning.AI
June 1, 2026 – Present
Introduction to Generative AI
Google Cloud
June 1, 2026 – Present
Oracle Cloud Infrastructure 2025 Foundations Associate
Oracle Cloud
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects showcase a diverse interest in AI/ML, IoT, and data engineering, indicating adaptability and a willingness to explore different technical domains. Participation in hackathons and technical clubs suggests a collaborative spirit and a proactive approach to learning and problem-solving. The breadth of skills and project types aligns with a growth-oriented culture, though the experience is primarily academic.
Soft Skills & Operational Fit
The candidate demonstrates initiative through participation in hackathons and competitive programming. Project descriptions suggest an ability to work on complex, multi-faceted problems. The internship at Capgemini indicates exposure to a professional work environment and foundational data integration concepts. However, the candidate's experience level is entry-level, and direct professional experience in a full-time software engineering role is limited.