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AI Engineer with less than a year in Computer Vision & GenAI
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Assessing your cultural and operational fit
Machine Learning & Full-Stack Engineer with experience in Computer Vision, GenAI (RAG Pipelines), NLP, and Time-Series Modeling. Skilled in Python, PyTorch, FastAPI, React, and OpenCV, with a focus on building scalable, production-ready AI and full-stack applications.
PDPM IIITDM Jabalpur
B.Tech
August 1, 2023 – June 30, 2027
Aerovania Pvt. Ltd.
Machine Learning Intern
October 1, 2025 – November 30, 2025
India
GirlScript Summer of Code (GSSOC)
Mentor (Project Admin)
August 1, 2025 – September 30, 2025
India
Multi-Document PDF Chatbot – RAG Pipeline
June 27, 2026 – Present
Built RAG pipeline with LangChain + Gemini-2.0-Flash + FAISS vector store; indexed 10,000+ chunks from 50+ PDFs with sub-second semantic retrieval (MiniLM-384). Engineered NLP ingestion pipeline using PyPDF2 + RecursiveCharacterTextSplitter; integrated HuggingFace embeddings for hallucination-controlled, context-aware QA responses.
View ProjectAI-Powered Hospital Admission System
June 27, 2026 – Present
Built hybrid healthcare AI pipelines using rule-based intelligence, TF-IDF, Logistic Regression, Random Forest, XGBoost, and agentic LLM reasoning for patient prioritization and ICU prediction. Developed FastAPI + PostgreSQL backend with Pydantic validation, caching, retry/fallback logic, JSON schema validation, and operational intelligence workflows.
Patent Published: In-Pipe Crack Detection Bot
Unknown
June 1, 2026 – Present
NIDAR Drone Innovation Challenge
Unknown
June 1, 2026 – Present
LeetCode - 100+ DSA problems solved
LeetCode
June 1, 2026 – Present
Electronics & Robotics Society - AI/ML Team Lead
Electronics & Robotics Society
June 1, 2026 – Present
HackerRank – SQL Intermediate (Intermediate)
HackerRank
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's involvement in GSSOC as a mentor and the Electronics & Robotics Society as an AI/ML Team Lead indicates a collaborative spirit and a willingness to contribute to a community. The diversity of projects (healthcare AI, chatbots, drone detection) and participation in innovation challenges suggest adaptability and a proactive approach to learning and applying skills, which aligns well with dynamic team environments. The candidate's profile shows a strong interest in practical application of AI, which is a good fit for an AI Engineer role.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through DSA achievements and project work. Mentorship experience indicates leadership potential and ability to collaborate. The focus on building production-ready AI systems suggests an understanding of operational aspects, though direct MLOps experience beyond basic Docker/Git is not extensively detailed.