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AI Engineer with less than a year in Artificial Intelligence & Machine Learning
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AI Intern with hands-on experience in building multi-output Random Forest pipelines for water quality prediction and performing EDA and feature engineering. Proficient in LangGraph, Pinecone, FastAPI, Streamlit, AWS Bedrock, Rekognition, Lambda, TensorFlow, and Xception CNN, applied in projects like autonomous research agents, multimodal sanitation reporting, and bone age estimation. Strong background in data structures, algorithms, machine learning, deep learning, and digital image processing.
IIITDM, Kancheepuram
B.Tech · Computer Science and Engineering (AI Major)
August 1, 2023 – June 30, 2027
AICTE-Shell-Edunet
AI Intern
June 1, 2025 – July 1, 2025
India
SanitiSense AI
June 1, 2026 – Present
Developed a multimodal sanitation reporting pipeline using Amazon Bedrock and Rekognition to classify civic issues from uploaded images. Implemented a RAG-based advisory workflow using Bedrock Knowledge Base and Titan embeddings for epidemic-risk insights and report generation. Integrated AWS Lambda, API Gateway, DynamoDB, and S3 to support report processing, storage, and AI-based validation workflows.
View ProjectBone Age Estimation
June 1, 2026 – Present
Trained an Xception-based CNN on 12,611 pediatric X-ray images for automated bone age prediction using transfer learning. Improved regression performance to R2 = 0.9169 and MAE = 9.04 months using mixed-precision training and optimized preprocessing. Evaluated gender bias and model interpretability through Grad-CAM visualizations and subgroup performance analysis.
View ProjectResearch Agent
June 1, 2026 – Present
Developed an autonomous research agent using LangGraph with planning, reflection, and validation loops for iterative query refinement. Integrated DuckDuckGo search, Python REPL execution, and Pinecone vector memory to automate financial and market research workflows. Deployed a Streamlit interface with structured JSON outputs and FastAPI endpoints for real-time interaction and response delivery.
View ProjectCultural Fit Analysis
The candidate's project diversity, ranging from environmental monitoring to medical imaging and autonomous agents, indicates a broad interest in applying AI to various domains. Participation in hackathons and competitive programming suggests a drive for continuous learning and a collaborative spirit. The focus on AI-related projects and coursework aligns well with an AI Engineer role, demonstrating a clear passion and commitment to the field. The candidate's profile suggests a proactive and innovative mindset, which would be a good cultural fit for a forward-thinking AI team.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through diverse project work. The ability to work on complex, multi-faceted AI projects suggests good analytical and critical thinking. The internship experience, though brief, indicates an ability to contribute to structured projects. The candidate's involvement in hackathons and competitive programming suggests a proactive and collaborative attitude, which aligns well with operational fit in a dynamic team.