AI Engineer with less than a year in NLP, Machine Learning & Data Analysis.
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Assessing your cultural and operational fit
Highly motivated Data Science student with practical experience in developing AI-powered solutions, managing data pipelines, and implementing machine learning models. Proficient in Python, SQL, and various ML/AI libraries, with a strong focus on Natural Language Processing and explainable AI. Eager to contribute analytical and problem-solving skills to innovative data and AI initiatives.
FAST NUCES
Bachelor of Science · Data Science
August 1, 2021 – June 30, 2025
LGS
A-Levels
June 1, 2019 – May 31, 2021
LACAS
O-Levels
June 1, 2016 – May 31, 2019
FAST NUCES
Teaching Assistant (Information Security)
September 1, 2025 – Present
Lahore, Punjab, Pakistan
Netsol
AI/DS Intern
June 1, 2025 – July 31, 2025
Lahore, Punjab, Pakistan
PetNutriCare (Final Year Project)
January 1, 2025 – December 31, 2025
• Developed an AI-powered nutrition system that generates personalized meal plans for pets and farm animals by using NLP to extract health insights from unstructured veterinary records and prescriptions. • Integrated an intelligent chatbot using the Gemini API to provide real-time guidance on animal profiles and nutritional guidance, supported by Explainable AI (SHAP/LIME) to give transparent, visual reasons for every food recommendation. • The system has been successfully implemented and tested across 10 core functional modules, achieving a 100% test case pass rate with 0% defect density., ensuring the system reliably identifies animals that need special care.
AI Intelligent Snake Solver
January 1, 2025 – December 31, 2025
• Developed an end-to-end ML system auditing pathfinding agents by training six models on 4.5M game steps, achieving 97% action prediction accuracy across multiple environments. • Applied SHAP explainability to differentiate navigation and risk patterns, identifying a 39% performance drift in A* to simulate production-level distribution shifts. Architected a full ML lifecycle featuring a Streamlit dashboard, MLflow tracking, and GitHub Actions for automated deployment and monitoring.
ScholarGraph
January 1, 2025 – December 31, 2025
• Built ScholarGraph, an autonomous multi-agent LLM system using LangGraph that analyzes scientific papers with adaptive summarization (Beginner/Intermediate/Expert levels). Implemented intelligent fallback between Gemini and Groq APIs with local FAISS vector search, eliminating external embedding dependencies. • Engineered comprehensive evaluation framework featuring hallucination detection, multi-dimensional quality scoring (Accuracy/Completeness/Clarity 1-5), and readability metrics (Flesch Reading Ease). Built iterative refinement loops with automatic citation extraction and section detection. • Developed end-to-end web app with real-time processing, multi-LLM comparison framework (Groq/Gemini/Cohere/Cerebras), visual analysis via Gemini Vision, PDF report generation, conversational RAG chatbot, and graceful error handling across 4+ LLM providers.
Cultural Fit Analysis
The candidate's project portfolio showcases a strong interest and capability in cutting-edge AI technologies, aligning well with an AI Engineer role. The diversity of projects, from pet nutrition to scientific paper analysis and game AI, indicates a broad intellectual curiosity and adaptability. The academic background in Data Science further strengthens the fit. The candidate's involvement in academic and personal projects suggests a self-driven and continuous learning mindset, which is valuable for cultural fit in an innovative environment.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills and an ability to work on complex, multi-faceted projects. Their experience as a Teaching Assistant suggests good communication and mentoring abilities. The project descriptions indicate a proactive and innovative approach to developing AI solutions. However, the resume does not provide explicit details on teamwork dynamics or stress handling in a professional setting, which would typically be assessed in a psychometric test.