خالد آل دوســـــري
Khalid Al Dosari
CS Student | Data Scientist | AI Engineer
Tuwaiq Academy Alumnus
CS Student | Data Scientist | AI Engineer
Tuwaiq Academy Alumnus
Senior computer science student and Tuwaiq Academy alumnus, focusing on applied data science,
AI Engineering, and MLOps. Experienced in building end-to-end solutions built with python,
machine learning, deep learning, RAG, LLMs, generative AI, and agentic workflows, with a
proven track record in building scalable, production-ready systems that turn raw data into
actionable
insights and real-world impact.
I've also spent nearly four years supervising operations for some of Saudi Arabia's biggest and most prestigious events, also volunteering and leading in student clubs. That experience taught me how to lead under pressure, coordinate across teams, and solve problems in real time, skills that translate directly into any environment.
Building and Developing AI Models Bootcamp
June 2026 - present
Bachelor's degree, Computer Science
August 2022 - present
Developed an end-to-end agentic automated machine learning pipeline leveraging Python, LangChain, FastAPI, Next.js, Modal, React and TypeScript; built a full MLOps stack enabling users to upload raw datasets, train custom models, and deploy production-ready cloud APIs via Modal.
Designed an agentic recommendation system with python, Node.js, MongoDB, JavaScript, HTML and CSS that parses PDF/text academic transcripts and maps historical grade distributions, therefore increasing recommendation alignment based on user-specific academic history.
Developed an AI-powered tourism analytics platform for the PwC Empowerthon, securing 4th place out of 11 teams. Integrated a bilingual AI demo, ROI calculator, and analytics dashboard using React, TypeScript, Vite, Supabase and JavaScript, it is aimed at helping Saudi destination owners turn visitor data into actionable insights with an AI demo, ROI calculator, analytics dashboard, and bilingual support.
Engineered a credit card cashback optimization algorithm in Java to implement and benchmark Brute Force (O(nm)) against Greedy (O(n*m)) approaches to demonstrate performance trade-offs.
Implemented and compared Backtracking, Forward Checking, and Maintaining Arc Consistency (MAC) algorithms with Java, Spring Boot, Maven, JavaScript, HTML and CSS to solve complex Constraint Satisfaction Problems (CSPs).
Engineered a deterministic context-free grammar parser with Java, Spring Boot, Maven, and JavaScript constructing full canonical LR(1) item sets and successfully merges same-core states into a functional LALR table. Containerized the backend application using Docker and exposed the parser mechanics via a REST API to a custom visualization interface.
CCIS Student Advisory Council
September 2025 - Present
THA Staffing
Jan 2026 - Present
Webook
October 2024 - November 2025
