AI Engineer with less than a year in Computer Vision & NLP
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Engineering student with industry experience building data-driven applications for visual inspection, document analysis, and process automation. Skilled in PyTorch, YOLOv11, Flask, MongoDB, Docker, LangChain, Roboflow, and n8n. Contributed to large-scale systems handling 10,000+ records while achieving up to 99% prediction accuracy. Strong background in predictive modeling, feature extraction, backend integration, distributed services, and end-to-end deployment of scalable solutions.
Lovely Professional University
Bachelor of Technology · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Droom Technology Pvt. Ltd.
Machine Learning Intern
December 1, 2025 – Present
Gurgaon, Haryana, India
AI Research Assistant
May 1, 2026 – June 1, 2026
Built a Retrieval-Augmented Generation (RAG) assistant over 1,000+ technical documents using LangChain and ChromaDB. Reduced information retrieval time by 80% through semantic search and vector embeddings. Implemented conversational memory and citation-aware responses, serving 500+ user queries. Exposed REST APIs through FastAPI for scalable integration with external applications.
Vehicle Inspection System
January 1, 2026 – March 1, 2026
Built an end-to-end AI vehicle inspection platform processing 5,000+ vehicle images and achieving 95%+ damage detection accuracy using YOLOv11. Designed a repair cost prediction engine using CatBoost regression models, improving estimation accuracy and reducing dependency on manual inspection effort. Engineered a computer vision pipeline processing 1,000+ vehicle videos, extracting frames and metadata for inspection workflows. Managed an asynchronous processing system supporting concurrent inspection requests using Flask, RabbitMQ, and MongoDB.
Oracle AI Autonomous Database
Oracle
October 1, 2025 – Present
Data Structures and Algorithms Interview Preparation
Cipherschools
September 1, 2024 – Present
Generative AI for Everyone
DeepLearning.AI (Coursera)
June 1, 2024 – Present
Prompt Engineering for ChatGPT
(Coursera)
April 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from RAG assistants to vehicle inspection systems, indicates a broad interest in applying AI to different domains. Their proactive pursuit of certifications in Generative AI and Prompt Engineering shows a commitment to continuous learning and staying current with emerging technologies. The internship experience at Droom Technology Pvt. Ltd. aligns well with industry-focused AI development, suggesting a practical, results-oriented mindset. The breadth of technical skills, including various programming languages, frameworks, and tools, points to adaptability and a willingness to explore different solutions.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through project descriptions, tackling real-world challenges like vehicle inspection and information retrieval. Their experience with containerization and microservices suggests an understanding of operational best practices for deploying AI solutions. The use of n8n for automation workflows indicates an ability to integrate AI components into broader business processes. Collaboration is implied through Git/GitHub usage for managing multiple AI projects.