AI Engineer with 1+ years in Computer Vision & Natural Language Processing
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Highly motivated AI Engineer with 1.0 years of experience specializing in Computer Vision, YOLO, CNN, LLM, and RAG. Proficient in Python, data analysis, and machine learning, with a strong background in developing interactive games, AI-powered drawing recognition, and developer productivity tools. Proven ability to lead projects, deliver production-ready solutions, and contribute to advanced AI and machine learning initiatives.
Texas College of Management and IT
Bachelor of Information Technology (Hons) · Information Technology
August 1, 2022 – June 30, 2026
Xavier International College
+2 Levels Science · Physics
June 1, 2015 – May 31, 2017
Frost Digital Ventures
AI Intern
November 1, 2025 – January 1, 2026
Lampati, Lumbini Zone, Nepal
Danson Solutions
Computer Vision Intern
May 1, 2025 – August 1, 2025
Kathmandu, Bagmati Zone, Nepal
Projector Camera Interactive Balloon Pop Game
January 1, 2024 – June 1, 2024
An interactive balloon-popping game that uses computer vision (YOLO object detection via ONNX), OpenCV, and Pygame to detect and respond to real-world interactions projected onto a screen, with threading for real-time camera capture and smooth gameplay. The system supports camera calibration, perspective correction, and multi-monitor/projector setups, and features animated visuals, sound effects, and score tracking, with assets managed in a structured directory. The technical stack includes Python, Pygame for graphics and event handling, OpenCV for camera and image processing, Ultralytics YOLO for object detection, and threading for efficient parallel camera frame acquisition.
View ProjectQuickDraw Game - AI-Powered Drawing Recognition
January 1, 2024 – June 1, 2024
Full-stack AI-powered drawing game: users draw objects on a smooth, responsive Vanilla JS canvas with real-time feedback, recognized by a CNN model integrated via FastAPI and Keras/TensorFlow for multi-class classification and confidence calibration. Comprehensive API endpoints for drawing recognition, random object selection, and model info; model training and calibration handled in Jupyter notebooks, with detailed results, confidence scores, error handling, mobile support, and clear project structure for easy deployment.
View ProjectDeveloper Copilot: AI-Powered RAG and PR Summarization
January 1, 2024 – June 1, 2024
An intelligent developer productivity suite featuring code search and pull request summarization, leveraging advanced natural language processing, vector search, and Retrieval-Augmented Generation (RAG) for comprehensive, context-aware codebase navigation and review. Implements PR summarization by executing Git commands to extract atomic code changes, enabling precise, commit-level analysis and generating concise, context-rich summaries for each pull request. The technical stack includes Python for backend logic, ChromaDB for vector storage, Groq API (Llama-3.3-70B-Versatile) for language understanding, RAG for improved search, and TypeScript for VS Code extension development, with structured assets and documentation for easy deployment and extension.
View ProjectMCQ Paper Grader
January 1, 2024 – June 1, 2024
Developed a web-based application to automate grading of multiple-choice answer sheets using image processing. Utilized OpenCV for bubble detection, Streamlit for an interactive user interface, and Pandas for result analysis and visualization.
View ProjectAI Internship Experience Letter
Frost Digital Ventures
January 1, 2026 – Present
Computer Vision Internship Letter
Danson Solutions
August 1, 2025 – Present
Sequence Models
DeepLearning.AI
March 19, 2025 – Present
Convolutional Neural Network
DeepLearning.AI
March 10, 2025 – Present
Structuring Machine Learning Projects
DeepLearning.AI
March 4, 2025 – Present
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization
DeepLearning.AI
February 27, 2025 – Present
Neural Networks and Deep Learning
DeepLearning.AI
February 13, 2025 – Present
Deep Learning Specialization
Coursera
February 1, 2025 – Present
Cultural Fit Analysis
The candidate's involvement in multiple personal projects, hackathons, and internships showcases a strong passion for AI and continuous learning. The diversity of projects (computer vision games, RAG systems, drawing recognition) indicates adaptability and a broad interest within the AI domain. Their proactive pursuit of certifications from DeepLearning.AI further reinforces a self-driven learning culture. The collaborative nature of their hackathon wins suggests a team-oriented mindset.
Soft Skills & Operational Fit
The candidate demonstrates problem-solving, data analysis, project management, and team collaboration skills through their project descriptions and hackathon participation. Their ability to lead a team on an interactive game development project during an internship suggests good operational fit for collaborative environments. The detailed project descriptions indicate a structured approach to development and documentation.