Abubeker Shamil
Addis Ababa, Ethiopia
Embedded Files
Hawassa University
(2016-2021)
BSc. (Electrical And Computer Engineering)
BSc. (Electrical And Computer Engineering)
Email: abubekershamil123@gmail.com
Generative AI
Generative AI
NLP
LLM Fine-Tuning
Prompt Engineering
Sentiment Analysis
Text Generation
OpenAI GPT APIs
Hugging Face
LangChain
LLamaIndex
Vectorstore (Weviate)
Automation Tools
Automation Tools
GitHub Actions - CI/CD
Docker
Bash
PowerShell
MLFlow
Airflow
DBT
AWS
ELT/ELT Pipeline
Programming
Programming
Python
React.js
Java
C++
SQL
FastAPI
TensorFlow
PyTorch
Git
Other Skills
Other Skills
Project Management
Agile Methodologies
Scrum
Technical Writing
Documentation
Teamwork
Analytical Thinking
Learning Technologies
Flexibility in Roles
About me
Abubeker Shamil is a dedicated Software Engineer with proven leadership skills. Proficient in Python, JavaScript, fine-tuning LLMs, RAG systems, prompt engineering, Langchain, and various frameworks. Known for a problem-solving mindset, effective communication skills, and a collaborative attitude. Passionate about Generative AI and Technology, with experience in developing advanced NLP systems and optimizing data workflows.
Education
Education
- Hawassa University (2016-2021)
BSc. (Electrical And Computer Engineering)
BSc. (Electrical And Computer Engineering)
Courses Taken
Assembly Language
Embedded Systems
Operating Systems
Data Structure and Algorithms
Object Oriented Programming
Computer Architecture
Control Systems
- 10 Academy (Apr - Sept 2024)
Generative AI and Machine Learning
Generative AI and Machine Learning
Courses Taken
Building a RAG Pipeline
Finetuning LLMs
Prompt Engineering
ML Engineering
Data Engineering
Technical Writing, Collaboration, Teamwork, and Communication
Designed and developed a user-friendly, interactive form that significantly improved the user experience while reducing form abandonment rates and increased submission completion rates.
Built an email delivery system to automate the receipt of vendor requirements and registrations.
Streamlined internal processes, improving efficiency by 35%.
Eliminated the need for paid form services such as Typeform and Google Forms, resulting in annual savings of approximately $850.
Reduced manual processing time of Excel sheets by 20%, saving the internal team an estimated 10 hours per week.
Skills Developed Continuous Integration and Continuous Delivery (CI/CD) · Back-End Web Development · Front-end Development · Vue.js · Email Server Setup · Customer centric Design
Launched apps on the Play Store, surpassing 100+ downloads.
Drove notable increase in user engagement via innovative app features
Achieved engagement growth by 61% by increasing the online presence.
Led a team 3 engineers to develop a livestreaming feature integrated into the app.
Skills Developed Project Management · Management · Software Development · Recruiting · Technical Recruiting, Mobile Application Development Lifecycle
Projects
Projects
Building an Efficient Retrieval Augmented Generation (RAG) System for Legal Document — Q&A Chatbot
Building an Efficient Retrieval Augmented Generation (RAG) System for Legal Document — Q&A Chatbot
Built a RAG system tailored for answering questions about legal documents. We covered the end-to-end workflow, from setting up the backend with FastAPI and Frontend with React to evaluating different configurations using RAGAS.
Visualization for Everyone: Redash Chatbot for Advanced Data Analytics, Visualization, and Insight Extraction
Visualization for Everyone: Redash Chatbot for Advanced Data Analytics, Visualization, and Insight Extraction
Our project integrates NLP into Redash, allowing non-technical users to analyze data using everyday language, eliminating the need for SQL knowledge. This speeds up decision-making, enhance productivity and sets the stage for advanced AI analytics.
Precision RAG: Building Enterprise Grade RAG Systems
Precision RAG: Building Enterprise Grade RAG Systems
The effectiveness of AI models hinges on the quality of prompts they receive, making prompt engineering a critical skill. To address this challenge, our project focuses on developing an enterprise-grade Retrieval-Augmented Generation (RAG) system that automates prompt generation, evaluation, and testing.
Data Engineering Tech Stack PostgreSQL, Airflow, Redash and DBT
Data Engineering Tech Stack PostgreSQL, Airflow, Redash and DBT
Developed a scalable data warehouse using ELT with DBT, orchestrated workflows with Apache Airflow, and visualized insights through Redash to revolutionize urban traffic management by harnessing data from UAVs and roadside cameras, enhancing city life through improved traffic flow.
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