AI Engineer with less than a year in machine learning & LLM applications.
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Motivated Python Full stack Engineer and final-year B.E. IT student (2026) with hands-on experience in machine learning, LLM applications, multi-agent AI systems, and workflow automation. Skilled in Python, FastAPI, LangChain, LangGraph, TensorFlow, Docker, AWS, and scalable AI workflows. Experienced in building end-to-end AI systems including RAG pipelines, conversational AI platforms, analytics automation, and intelligent reporting solutions.
P.E.S. Modern College of Engineering, Pune
B.E. · Information Technology
August 1, 2023 – June 30, 2026
Govt. Polytechnic, Nanded
Diploma · IT
N/A – Present
Lets Grow More
Machine Learning Intern
December 1, 2025 – June 1, 2026
India
Autonomous AI Operations Platform – Multi-Agent Workflow Automation System
June 1, 2026 – Present
Built a multi-agent AI platform capable of intelligent task routing, document RAG, dataset analytics, report generation, and automated email workflows. Implemented conversational multi-agent AI workflows with memory, contextual follow-up handling, streaming execution logs, and autonomous task orchestration. Integrated LLM-powered orchestration using LangGraph and LangChain with tool execution for web search, API calling, memory retrieval, and document analysis. Built full-stack architecture using FastAPI backend and React frontend with scalable modular agent workflows.
View ProjectFood Spoilage Detection – Production-Ready AI Web Application
June 1, 2026 – Present
Built and optimized a CNN-based image classification model achieving 94% accuracy to classify food as Fresh / Near Spoilage / Spoiled. Performed data preprocessing, augmentation, feature extraction, and model evaluation. Developed FastAPI-based REST endpoints for real-time image inference. Dockerized and deployed the application on AWS EC2 for scalable production use.
View ProjectUS Visa Approval Prediction – Data-Driven Decision System
June 1, 2026 – Present
Designed a complete ML pipeline including data cleaning, feature engineering, model training, and validation. Evaluated multiple models and optimized performance for better accuracy and interpretability. Built REST APIs to serve predictions in real time. Deployed the system on AWS using Docker, enabling client-ready inference.
View ProjectCareer Essentials in Generative AI
Microsoft & LinkedIn
June 1, 2026 – Present
Data Science and Analytics
HP
June 1, 2026 – Present
Digital Skills: Artificial Intelligence
Accenture
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects are diverse within the AI/ML domain, covering multi-agent systems, image classification, and predictive modeling. This breadth, combined with certifications in Generative AI and Data Science, indicates a strong interest in continuous learning and adaptability. The target role is an internship, which aligns well with the candidate's current experience level and educational status. However, the focus on Python and SQL is strong, but specific experience with CrateDB is not mentioned, which might require some ramp-up.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on end-to-end solutions, from model development to deployment. The internship experience, though brief, mentions working in an Agile environment and using Git/GitHub, suggesting an understanding of collaborative development practices. The detailed project descriptions demonstrate good communication of technical work.