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AI Engineer with less than a year in AI/ML and Python.
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Assessing your cultural and operational fit
Detail-oriented Data Science Engineer with hands-on experience in machine learning, deep learning, and generative AI. Proficient in Python, TensorFlow, Keras, and various data manipulation and deployment frameworks. Skilled in developing AI-powered solutions, from chatbots with persistent memory to disease classification and anomaly detection systems. Eager to apply strong analytical and technical skills to drive impactful data-driven projects.
Government Engineering College Modasa
Bachelor of Engineering · Computer
N/A – June 30, 2025
Evoastra Ventures Pvt Ltd
Data Science Intern
December 1, 2025 – January 31, 2026
India
Ibtida Tech Pvt Ltd
Data Science Intern
November 1, 2025 – December 31, 2025
India
BIT Infotech Pvt Ltd
Data Science Intern
January 1, 2025 – April 30, 2025
Vadodara, Gujarat, India
AI Newsletter Automation System
January 1, 2025 – Present
Built an automated AI/ML news aggregation system integrating 4 external APIs (NewsAPI, MediaStack, WebZio, GitHub API) to collect and filter up to 150+ daily articles. Developed a Streamlit interface enabling preview, local HTML generation, timestamp-based file saving, and one-click download for automated content publishing workflows.
Stateful AI Chatbot with Persistent Memory
January 1, 2025 – Present
Built a stateful LLM chatbot using LangGraph State Grap with persistent memory via SQLite checkpointing. Enabled seamless conversation retrieval and state restoration using LangGraph's checkpoint system for improved user experience. Integrated Groq LLM (LLaMA 3.1) via LangChain for fast and efficient real-time responses. Developed an interactive frontend using Streamlit with chat-style UI and sidebar-based thread navigation. Designed multi-thread conversation management with unique session IDs, supporting persistent chat history across sessions.
Cotton Plant Disease Classification
January 1, 2025 – Present
Built a deep learning-based image classification system using VGG16 CNN to classify cotton images into 4 categories (diseased leaf, diseased plant, fresh leaf, fresh plant). Achieved 99% training accuracy and 96.2% validation accuracy through optimized preprocessing and model tuning. Implemented real-time prediction with image resizing, normalization, and inference using Flask web application. Enabled user-driven image upload and probability-based classification for practical agricultural disease detection.
Dewang Mehta IT Award – Topper
Unknown
August 1, 2025 – Present
DataScience Certificate
BIT Baroda
May 1, 2025 – October 1, 2025
Cultural Fit Analysis
The candidate's portfolio showcases a strong interest in cutting-edge AI technologies (LLMs, Generative AI) and practical applications. The personal projects demonstrate initiative and self-driven learning, which aligns well with an innovative and fast-paced environment. The internships, though short, indicate exposure to different problem types (time-series, NLP, classical ML), suggesting a broad interest in data science and AI, which can contribute positively to team diversity and knowledge sharing.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a structured approach to problem-solving and an ability to work on end-to-end AI/ML solutions, from data ingestion to deployment. The detailed descriptions suggest good communication of technical processes. The variety of projects and internships implies adaptability and a willingness to learn diverse domains within AI/ML.