AI engineer

NAYABB FATIMA

Dubai, UAE +971-********* *************@*****.***

LinkedIn: linkedin.com/in/nayabb-fatima-9b177a55/ GitHub: github.com/Nayab-zak PROFESSIONAL SUMMARY

AI Engineer (Applied AI & Machine Learning) with 5+ years of experience designing, developing, and deploying scalable AI/ML systems for industrial optimization, enterprise automation, and computer vision applications. Proven expertise in machine learning, deep learning, optimization (MILP), time series forecasting, and Large Language Models (LLMs/RAG systems).

Hands-on across the full AI lifecycle—problem formulation, model development, optimization, and production deployment—delivering measurable business impact, including 40% reduction in planning time and 25% improvement in resource utilization.

Experienced in building production-grade ML pipelines, MLOps systems, and AI-powered decision support platforms using Python, PyTorch, TensorFlow, FastAPI, Docker, and SQL. PhD researcher (in progress) focused on AI-driven medical diagnostics, with strong interest in applied AI for large-scale industrial optimization and intelligent decision systems.

TECHNICAL SKILLS

AI & Machine Learning Deep Learning, Machine Learning, Reinforcement Learning, NLP, Large Language Models (LLMs), RAG Systems, Computer Vision, Predictive Modeling, Time Series Forecasting, ML Pipelines, MLOps

Optimization & OR MILP Optimization, Heuristic Algorithms, Resource Planning, Scheduling, Allocation Optimization

Programming Python, MATLAB, SQL (PostgreSQL, MySQL), FastAPI, RESTful API, TypeScript Frameworks TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, LangChain, TRL, PEFT

Tools & Platforms Docker, AWS, Git, GitHub, Streamlit, Jupyter, Anaconda PROFESSIONAL EXPERIENCE

AI Specialist Jan 2024 – Present

DP World JAFZA, Dubai, UAE

Led the design and deployment of an AI-driven vessel and yard planning system integrating time series forecasting with MILP optimization, reducing container planning time by 40% and improving space utilization by 25% in large-scale port operations.

Developed end-to-end production ML pipelines and decision support systems using Python, PostgreSQL, and FastAPI, enabling real-time data processing and optimized resource allocation. Built a domain-specific RAG-based AI chatbot for operational knowledge management, improving decision- making accuracy by 35%.

Collaborated with cross-functional engineering and operations teams to integrate AI solutions into existing enterprise systems, ensuring scalability, reliability, and performance. LLM Engineer Sep 2023 – Jan 2024

Gasame (Remote)

Designed and fine-tuned domain-specific Large Language Models (LLMs) for enterprise applications, improving response accuracy by 40% through advanced prompt engineering and fine-tuning strategies. Implemented PEFT and LoRA-based optimization techniques to enhance model efficiency and performance for production use cases.

Senior AI Engineer Aug 2023 – Dec 2023

SOCO Engineers Multan, Pakistan

Managed development and deployment infrastructure for scalable AI systems, ensuring reliability across distributed environments.

Performed statistical analysis and predictive modeling to support strategic decision-making, improving operational efficiency by 25%.

Senior AI Engineer Aug 2022 – Jul 2023

iEKOMEDIA (Remote)

Designed and deployed a computer vision-based retail analytics system, achieving 92% accuracy in customer behavior prediction and enabling data-driven store optimization. Built and optimized end-to-end machine learning pipelines, reducing training time by 20% and improving model accuracy by 15%.

Mentored a team of 4 AI engineers and established best practices for ML model development, deployment, and MLOps workflows.

AI Engineer May 2021 – Jul 2022

Quantsys (Remote)

Automated infrastructure for data science workflows, increasing team productivity through streamlined CI/CD pipelines.

Developed scalable data transformation and ingestion systems processing terabytes of data daily. Built predictive AI models for business-critical decisions. SELECTED PROJECTS

• Email Agent System: Production-grade multi-agent RAG system for automated email processing, intelligent data extraction, and response generation using LangChain and custom retrieval pipelines.

• Qwen2.5 Vision-Language Model Fine-Tuning Pipeline: Developed modular pipeline for fine-tuning VLMs using PEFT, quantization, and efficient training strategies for domain-specific applications.

• Multi-Agent RAG System (onprem_rag_chatbot): Built modular multi-agent LLM architecture with web search integration, image generation, and context-aware response synthesis.

• Database & API Integration: Designed PostgreSQL schema and implemented FastAPI-based microservices architecture for seamless integration between AI agents and frontend systems.

• Blood Leakage Detection & Classification: Developed hybrid computer vision + deep learning system for retinal image analysis supporting clinical decision-making.

• Brain Tumor Segmentation & Grading: Built deep learning model (U-Net) for medical image segmentation and classification with high accuracy.

EDUCATION

PhD in Computer Science 2021 – Present

Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad Research: Automated diagnosis of retinopathy using machine learning and AI M.S. in Electrical and Computer Engineering 2015 – 2018 COMSATS University, Islamabad

B.S. in Electrical and Computer Engineering 2009 – 2013 COMSATS University, Lahore

SELECTED RESEARCH & PUBLICATIONS

• "Automatic optic disk detection and segmentation by variational active contour estimation in retinal fundus images" – Medical image processing and computer vision

• "Gunshots Localization and Classification Model Based on Wind Noise Sensitivity Analysis Using Extreme Learning Machine" – Signal processing and applied ML CERTIFICATIONS

• Deep Learning Specialization – Coursera/deeplearning.ai (2023)

• Machine Learning Engineering for Production (MLOps) – Coursera (2022) LANGUAGES

English (Fluent), Urdu (Native)

Contact this candidate