Jeddah, Saudi Arabia

Abdulrahman Alshahrani

Research-driven. System-oriented. Builder at heart.

Exploring machine learning, distributed computing, and web development to craft elegant solutions.

Tech Stack

Tools & Technologies

Languages

Python Go TypeScript JavaScript C C++ SQL

Machine Learning

PyTorch scikit-learn Pandas OpenCV RAG Systems Flower

Web Development

React Next.js FastAPI Shadcn SQLAlchemy Streamlit PostgreSQL SQLite

DevOps & Cloud

Docker Docker Compose Google Cloud Cloudflare OpenTelemetry Linux Git SSH
Education

Academic Background

KAUST

MS in Computer Science

King Abdullah University of Science and Technology

LLMs, Agentic AI, Concurrency, Computer Networks

UT Austin

BS in Computer Science

The University of Texas at Austin

High Performance Computing, Virtualization, Cloud Computing

Experience

Where I've Worked

Aramco

ML Engineer Intern

Aramco · Thuwal, Saudi Arabia

  • Developed foundation models to predict rock properties, handling data collection and multi-GPU training.
  • Built an OCR and barcode pipeline to extract serial numbers from rock samples.
  • Created a Streamlit and SQLite system to manage collected data for a digital rock sample archive.
Longhorn Developers

Software Engineer

Longhorn Developers · Austin, Texas

  • Contributed to UT Registration Plus, a React application used by 50k+ students to facilitate course registration.
  • Added direct course registration through the app, handling sign-in flows and data scraping logic.
Aramco

ML Engineer Intern

Aramco · Thuwal, Saudi Arabia

  • Enhanced the synthetic data for a Computer Vision model by creating 3D renders in Blender.
  • Captured and integrated 360° images to produce more realistic datasets, boosting model accuracy by 20%.
  • Created a flexible PyTorch evaluation repo for evaluating different state-of-the-art computer vision models.
UT Austin

Undergraduate Course Assistant

UT Austin · Software Engineering Class

  • Supervised 6 student groups in developing full-stack websites, guiding them with project architecture design.
  • Reviewed and provided feedback on 30+ weekly student blogs, monitoring progress and reporting summaries to the professor.
  • Conducted weekly office hours to assist students with understanding course concepts and fixing technical issues.
  • Rewrote the auto-grading script with proper error handling, reducing grading time to about 5 minutes per assignment.
USC

Research Intern

USC Viterbi School of Engineering · Data Science Lab

  • Implemented the Canonical Polyadic (CP) tensor decomposition algorithm using the Tensor Algebra Compiler and ran experiments on arbitrary datasets, achieving over 90% compression while preserving statistical significance.
  • Presented the algorithm and results at a department-wide symposium.
Projects

Featured Work

Distributed Multi-Agent Systems

Designed a multi-agent framework compiling apps into different infrastructure configurations with RAG, persistent memory, and built-in observability.

Go Docker Compose OpenTelemetry RAG Vector Stores

Agentic Context Engineering

Reproduced the Agentic Context Engineering framework with observability and cost-saving optimizations by routing requests to cheaper models while maintaining accuracy.

Python OpenTelemetry OpenRouter

Federated Learning With Malicious Clients Tolerance

Built a Federated Learning framework using Flower with a VAE-based aggregator for detecting malicious clients via anomaly detection, deployed on Google Cloud for realistic benchmarking.

Flower PyTorch Google Cloud
Code

GILD Mail

Developed a paid messaging platform enabling user-to-user email communication with integrated balance management and transaction fees tracking.

Next.js Stripe Supabase SendGrid

The Word Engineer

Participated in a 3-month competition (SDAIA) to enhance ALLaM, a large Arabic language model, focusing on Arabic poetry generation improvements.

Flask React Python IBM Watson
Code

ML Energy Consumption Analysis Tool

Developed a Python-based tool using scikit-learn and CodeCarbon to analyze model accuracy vs. energy consumption during hyperparameter tuning.

Python Scikit-learn CodeCarbon
Code

California Wildfires

Collaborated with a team of 5 to develop a React web application with a MySQL database, showcasing data about wildfires, nearby fire protection facilities, and California counties.

React MySQL AWS Selenium
Code
Awards

Recognition

KAUST Gifted Student Program (KGSP) Scholarship

Contact

Let's Connect

Open for opportunities and collaborations.