Areeba Rashid

Machine Learning Engineer with hands-on experience designing and deploying AI agents and automated workflows using LLMs, RAG, and tool-using architectures. Proficient in Python and TypeScript-based integrations with APIs, databases, and Airflow and n8n pipelines to deliver production-ready solutions. Developed country-specific chatbots and a no-code resume screening system, ensuring reliability and observability for AI-driven products.

Machine Learning Engineer - VannGuard AI

(2025-01)

• Built RAG-powered AI agents using LLaMA, CrewAI, and LangChain to generate creative briefs from scraped country data.
• Automated Python-based web scraping pipelines using Apache Airflow, integrated with dynamic RAG storage and internal APIs for data retrieval.
• Developed and deployed country-specific chatbots using LLMs and FastAPI, integrating with internal APIs and databases.
• Designed a no-code workflow in n8n to automate ML resume screening: Parsed resumes with Groq-powered LLM → structured JSON (name, skills, experience, links, etc.); Created Drive folders per applicant, uploaded documents, and logged details to Google Sheets; Ranked candidates based on job-specific experience and tech-stack match.

Machine Learning Intern - NECOP (NESCOM)

(2024-01 - 2024-12)

• Developed CNN and ViT models for skin lesion classification with GradCAM explainability.
• Integrated LLM-based QA (Groq + Ollama) for medical support chat.
• Deployed Docker-based ViT training pipelines with GPU acceleration.

ML Intern (Part-time) - CogniMindAI

(2023-01 - 2024-12)

• Explored core ML libraries (NumPy, PyTorch, Matplotlib)
• Implemented CLIPSeg (HuggingFace) for zero-shot image segmentation.
• Built OCR pipelines using PyTesseract on scanned PDF records.
• Contributed to Titanic classifier, ride duration predictor, and LLM prototyping.

Quantum Research Intern - AITECH (NCP)

(2023-01 - 2023-12)

• Studied quantum computing concepts: superposition, entanglement, and quantum gates.
• Researched quantum gates, entanglement, and superposition via IBM Qiskit.
• Developed hybrid SVM-QSVM models integrating classical and quantum ML.

Quantum Computing Workshop - EME NUST

(2023-01 - 2023-12)

• Participated in a one-week hands-on workshop on quantum computing.
• Hands-on training on quantum algorithms via MATLAB and Amazon simulators.

QA Intern - Red Buffer Pvt Ltd

(2022-01 - 2022-12)

• Conducted frontend QA testing for real estate tax apps.
• Authored test cases, tracked bugs, and improved frontend quality.
• Transitioned to JavaScript development and practiced LeetCode for problem solving.

MS - Computer Science - Bahria University, Islamabad

BS - Computer Science - SZABIST Islamabad