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AI Engineer with less than a year in LLMs & Computer Vision
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Assessing your cultural and operational fit
AI/ML Engineer and M.Tech (Artificial Intelligence) candidate with strong hands-on experience in Large Language Models (LLMs), Generative AI, Computer Vision, and Augmented Reality (AR) applications. Proven ability to design, build, and deploy end-to-end AI systems including LLM-powered chatbots, retrieval-augmented generation (RAG) pipelines, and 3D AR experiences. Proficient in Python, PyTorch, TensorFlow, Hugging Face, and Docker, with a strong focus on building ATS-friendly, production-ready, scalable AI solutions.
Pandit Deendayal Energy University Gandhinagar
Master's Degree · Artificial Intelligence
July 1, 2024 – Present
Gujarat Technological University Gandhinagar
Bachelor's Degree · Computer Engineering
August 1, 2021 – May 1, 2024
Gujarat Technological University Gandhinagar
Diploma · Computer Engineering
August 1, 2018 – May 1, 2021
InfoLabz (InfoLabz IT Services Pvt. Ltd)
Data Science and Artificial Intelligence Intern
January 1, 2024 – May 1, 2024
Ahmedabad, Gujarat, India
QueryFinders (QueryFinders Solution)
Data Analytics Intern
July 1, 2023 – August 1, 2023
Ahmedabad, Gujarat, India
LLM-Based YouTube Video Chatbot (RAG System)
June 5, 2026 – Present
Built an LLM-powered conversational chatbot that allows users to interact with YouTube video content using natural language. Implemented Retrieval-Augmented Generation (RAG) by extracting video transcripts, generating embeddings, and storing them in a vector database. Integrated Hugging Face Transformers / OpenAI-style LLMs, semantic search, and prompt engineering for accurate contextual responses. Deployed the application using Streamlit and Docker, enabling real-time question answering over long-form video content. Tech Stack: Python, Hugging Face, FAISS, Streamlit, Gorq, pinecone.
View ProjectAugmented Reality (AR) Project – 3D Box Creation and Interaction
June 5, 2026 – Present
Developed an AR-based application for creating, visualizing, and interacting with 3D boxes in real-world environments. Implemented spatial mapping, object placement, and real-time rendering for immersive AR experiences. Focused on performance optimization and accurate 3D transformations. Use Cases: AR prototyping, education, and interactive visualization.
View ProjectCustomer Segmentation and Predictive Analysis for B2C Marketplaces
June 5, 2026 – Present
Built a data-driven customer segmentation model to analyze consumer behavior and predict purchasing trends. Used clustering and predictive analytics to enhance marketing strategies and customer engagement. Impact: Helped optimize business decision-making and targeted marketing campaigns.
View ProjectEEG-Based Motor Imagery Classification Using Deep Learning Techniques
IEEE ICCCNT
January 1, 2025 – Present
Data Analytics Job Simulation
Deloitte
January 1, 2025 – Present
Advanced NLP with Python for Machine Learning
LinkedIn Learning
January 1, 2024 – Present
Deep Learning Fundamentals with Keras
EDX IBM
January 1, 2024 – Present
AI for Everyone
EDX IBM
January 1, 2024 – Present
Python Basics for Data Science
EDX IBM
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including AR, LLM chatbots, and customer segmentation, shows a broad interest in various AI applications. Their academic background, including a Master's in AI, aligns well with a culture that values continuous learning and innovation. The teaching assistant role also suggests a willingness to contribute to knowledge sharing. The breadth of skills and technologies listed indicates adaptability and a strong desire to explore different facets of AI, which is a good fit for dynamic, research-oriented environments.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach to learning and skill development through numerous certifications and a published research paper. Their project descriptions indicate an ability to work on complex, multi-faceted problems. The internship experiences suggest an understanding of data-driven decision-making and operational workflows. However, without direct interview data, specific soft skills like teamwork, problem-solving under pressure, or communication in a team setting cannot be fully assessed.