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AI Engineer with less than a year in Generative AI, RAG, and Machine Learning
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Computer Science graduate specializing in Generative AI, Retrieval-Augmented Generation (RAG), and Machine Learning. Holds three Oracle AI certifications and has hands-on experience building LLM-powered applications, federated learning frameworks, and production-grade AI chatbots. Proficient in Python, TensorFlow, LangChain, and Hugging Face Transformers. Passionate about applying deep learning and NLP to solve real-world problems, particularly in healthcare and intelligent systems.
University
Bachelor of Science · Computer Science
August 1, 2022 – June 30, 2026
Emumba
Frontend Development Intern
July 1, 2024 – August 31, 2024
Islamabad, Islamabad Capital Territory, Pakistan
Aiodock
Web Development Intern
June 1, 2022 – August 31, 2022
Islamabad, Islamabad Capital Territory, Pakistan
Chatbot - Alzheimer's Health Assistant
January 1, 2026 – Present
Built an intelligent health assistant chatbot with real-time symptom extraction, health prediction, and adaptive multi-stage dialogue flow using LLM-powered backends. Integrated backend APIs for NLP-driven clinical assessment across structured diagnosis and open conversation modes.
View ProjectFederated Learning Framework for Healthcare
January 1, 2026 – Present
Designed a federated learning system to optimize node-level model performance across heterogeneous, distributed clinical datasets without sharing raw patient data. Implemented and benchmarked FedAvg and FedMA aggregation strategies; analyzed convergence stability and fairness across non-IID client nodes. Evaluated global model consistency using Accuracy, Precision, Recall, and F1-Score — demonstrated measurable reduction in inter-client performance variance.
MoodLoop - Multi-LLM Therapy Dialogue System
January 1, 2026 – Present
Engineered a Flask backend orchestrating real-time multi-turn conversations between three LLM personas (CBT, Holistic, Analytical), each with independent system prompts and context windows. Powered by Gemini Pro API with fully dynamic, zero pre-scripted responses; implemented context-aware dialogue management across multiple therapy topics. Applied RAG-style topic injection across five domains (Anxiety, Depression, Trauma, Work-Life Balance, Digital vs. Traditional Therapy) for grounded, coherent AI dialogue.
View ProjectOracle AI Vector Search Certified Professional
Oracle
June 25, 2026 – Present
Retrieval Augmented Generation (RAG)
Coursera
June 25, 2026 – Present
Oracle Cloud Infrastructure 2025 Certified Generative AI Professional
Oracle
June 25, 2026 – Present
Oracle Cloud Infrastructure 2025 Certified AI Foundations Associate
Oracle
June 25, 2026 – Present
Neural Networks and Deep Learning
Coursera / DeepLearning.AI
June 25, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from academic research in federated learning for healthcare to personal hackathon projects like a multi-LLM therapy system, indicates a broad interest and proactive approach to learning and applying AI. The focus on healthcare-related AI projects aligns well with roles requiring ethical considerations and real-world impact. The certifications in Oracle Cloud Infrastructure and Generative AI show a commitment to staying current with industry trends and cloud platforms, which is a good cultural fit for a dynamic tech environment.
Soft Skills & Operational Fit
The candidate's participation in university-level debates and presentations suggests strong communication and presentation skills. Their self-description as disciplined and goal-oriented aligns with a positive work attitude. The project descriptions indicate an ability to work on complex, multi-faceted problems, which is valuable for operational fit in an AI engineering role.