Temesgen Gebreabzgi
Addis Ababa, Ethiopia
Embedded Files
Gen AI Engineering
Gen AI Engineering
Prompt Engineering
RAG
Langchain
Vector databases
Pytorch
Tensorflow
Machine Learning
Machine Learning
EDA
Scikit-learn
Matplotlib
CNN & RNN
Keras
Computer vision
Software Engineering
Software Engineering
Python
JavaScript
Fast API
Flask
Tailwind CSS
Streamlit
Testing, Unit Testing
DevOps &MLops
DevOps &MLops
Docker
CI/CD
Mlops
DVC
MLflow
Apache Airflow
Apache Kafka
About me
Junior AI Engineer skilled in Generative AI, machine learning, and software development. Proficient in Python, PyTorch, TensorFlow, and Scikit-learn. Experienced in RAG, prompt engineering, and building scalable data pipelines. Dedicated to designing innovative AI-driven software systems for impactful global applications.
Education
- 10 Academy( Oct 2024 )
Generative AI Engineer
Generative AI Engineer
- Addis Ababa University ( July 2023 )
BSc. (Information Systems)
BSc. (Information Systems)
- Relevant courses
- Fundamentals of programming
- Relational Databases
- Object oriented programming
- Agile methodology
- SDLC
- Networking
- Project
- Monitor network traffic, enforced security policies, and configured firewalls and IDS/IPS
- Tested software products for bugs, operating speed, and performed vulnerability assessments’ which result to increase development efficiency by 20%
- Delivered security awareness training programs for employees
- Implemented RESTful APIs in React that enabled analytics team to increase reporting speed by 40%
- Built 2 scalable company websites using WordPress, that we delivered to clients
- Conducted System and User documentations
Projects
Develop an automated system that transforms textual descriptions of advertisement concepts and assets into detailed, visually compelling storyboards by integration of cutting-edge machine learning, natural language processing, and computer vision technologies to revolutionize the ad creation process.
Built a scalable data warehouse for Large Language Model (LLM) fine-tuning with a team of 5. Empowered Amharic language customer support and engagement using LLM capabilities. We've achieved this by fine-tuning the Llama model on a dataset of Amharic news articles scraped from various websites.
Build a reliable and scalable platform for crypto back-testing trading strategies. That leverages advanced time-series forecasting methods to predict future price trends with greater accuracy.
Developed a high-precision legal expert system for contract Q&A using RAG. The system leverages advanced NLP techniques to provide accurate and context-aware answers to questions about legal contracts.
Page updated
Google Sites
Report abuse