Fatima Malik

AI Engineer with hands-on experience building AI-powered applications and intelligent backend systems using Python, Django, Flask, LLMs, RAG, vector databases, and AI agents. Experienced in developing retrieval-augmented generation pipelines, integrating LLM APIs and local models, implementing embeddings and semantic search, and building real-time AI applications with WebSockets and Celery. Strong full-stack foundation across React.js and Python backends, with experience deploying containerized applications using Docker in Linux/Ubuntu environments.

Additional machine learning and computer vision experience with PyTorch, TensorFlow, YOLOv8, DINOv2, and OpenCV.

Junior AI Engineer at Fusion Cortex (2026-03 – Present)

• Developed AI-powered features for web applications using Python, Django, Flask, and REST APIs, integrating AI capabilities into production-oriented application workflows.
• Built AI agents and automation workflows with LangChain and LangGraph, integrating LLM APIs to automate information extraction and intelligent processing tasks.
• Improved LLM response quality and reliability through structured prompt engineering, iterative testing, and optimization workflows.
• Built RAG-based retrieval solutions using vector embeddings, FAISS, and ChromaDB to support context-aware information retrieval.
• Collaborated with cross-functional teams to develop containerized AI applications using Docker in Linux/Ubuntu environments.
• Troubleshot AI application issues and optimized system workflows across backend, retrieval, and LLM components.

AI Engineer Intern at Fusion Cortex (2025-12 – 2026-03)

• Built and validated RAG pipelines using vector embeddings and FAISS for document retrieval and AI-powered question-answering workflows.
• Contributed to LangChain-based LLM integrations and AI agent experiments through optimization, benchmarking, and performance evaluation.
• Curated and annotated datasets to support AI model development, testing, and experimentation.
• Developed data preprocessing workflows that improved the robustness and consistency of AI agent inputs on real-world data.

Machine Learning Intern at Corvit Systems (2024-05 – 2024-09)

• Developed and evaluated machine learning classification and regression models using TensorFlow and PyTorch, measuring performance on held-out test datasets.
• Designed controlled ML experiments to evaluate model performance and documented findings for technical knowledge sharing.
• Cleaned, preprocessed, and annotated datasets and applied augmentation techniques to improve model generalization and test reliability.

B.Sc. in Software Engineering – Government College University Faisalabad (2021 – 2025)