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AI Engineer with less than a year in Machine Learning & Deep Learning
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Assessing your cultural and operational fit
AI undergraduate with hands-on experience in Machine Learning, Deep Learning, Computer Vision, and LLM-powered applications. Skilled in developing AI systems including RAG chatbots, recommendation systems, and predictive models using Python and PyTorch. Passionate about building practical AI solutions and exploring opportunities in Machine Learning, Data Science, and Software Development.
COMSATS University Islamabad
Bachelors of Artificial Intelligence · Artificial Intelligence
September 1, 2022 – June 30, 2026
CognoRise InfoTech
Python development
July 1, 2024 – August 31, 2024
India
DreamAssist - AI Powered Educational Platform
January 1, 2026 – June 19, 2026
Developed a full-stack AI-based learning platform focused on personalized education and student well-being. Built an Adaptive Teaching Engine using RAG and LLMs for contextual tutoring. Implemented an AI Study Planner with dynamic scheduling, quizzes, flashcards, summaries, and spaced repetition. Integrated mental health monitoring for mood-aware learning and AI personas for interactive, motivational experiences.
HR Policy ChatBot & Invoice Parsing System
January 1, 2025 – December 31, 2025
Developed an intelligent HR policy chatbot and automated invoice parsing system using LangChain and vector databases. Implemented Retrieval-Augmented Generation (RAG) to enable accurate, context-aware document querying and efficient extraction of structured data from invoices.
Image Classification with CNN
January 1, 2025 – December 31, 2025
Designed and trained a Convolutional Neural Network (CNN) for robust image recognition using deep learning techniques. Optimized the model for high-accuracy feature extraction and classification, enabling efficient automated detection of image patterns.
Book Recommendation System
January 1, 2024 – December 31, 2024
Developed a machine learning-based book recommendation system using Python and Scikit-learn. Implemented multiple algorithms including KNN, Random Forest, SVM, and Linear Regression, supporting both content-based and collaborative filtering for personalized recommendations.
Introduction to Retrieval Augmented Generation (RAG)
Coursera
June 19, 2026 – Present
Generative AI with LLMS
Coursera
June 19, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from educational platforms to HR chatbots and recommendation systems, indicates a broad interest in applying AI across different domains. Participation in a hackathon suggests a collaborative and innovative mindset. The academic focus on AI aligns well with a company seeking an AI Engineer.
Soft Skills & Operational Fit
The candidate demonstrates problem-solving, analytical thinking, and collaboration skills through project descriptions and hackathon participation. Adaptability and continuous learning are also highlighted, which are crucial for an AI Engineer role. The operational fit appears good given the project-based experience.