Kibrewossen Tesera
Kibrewossen Tesera

Software Engineer

Open to offers · Member since 18 Oct 2026
Location
Addis Ababa, Ethiopia
Desired salary
Unspecified
Work preference
Remote Only
Experience level
Junior

About

Professional summary

I am a Software Engineer based in Addis Ababa, Ethiopia, with experience building scalable backend systems, machine learning solutions, and AI-powered applications. My primary programming language is Python, and I also work with JavaScript, TypeScript, C#, C++, and Java.

I have contributed to production software engineering initiatives, including migrating a legacy monolith to a Node.js and Docker-based microservices architecture. I build and optimize RESTful APIs, GraphQL endpoints, caching layers, and real-time messaging systems for high-traffic applications.

My machine learning and AI experience includes end-to-end ML pipelines, model evaluation, predictive modeling, RAG systems, LLM evaluation, fine-tuning, symbolic AI, and retrieval optimization. I have worked in AI research environments using MOSES and MeTTa while improving Python code quality and evaluator performance.

I enjoy developing practical products from the ground up, including machine learning libraries, multilingual customer-support platforms, Telegram moderation bots, and social applications. I focus on modular architecture, clean code, reliability, performance, and maintainable development workflows.

I am comfortable collaborating remotely and using modern engineering practices, including Git, GitHub Actions, Docker, database design, API development, and automated workflows. I am interested in software engineering, backend engineering, machine learning engineering, and applied AI opportunities.

Skills

28 capabilities

Tech stack & tools

Working toolkit

Application Hosting

Languages & Frameworks

Experience

Career history

Software Engineer Zemenay Tech

Led the migration of a legacy monolithic application to a microservices architecture using Node.js and Docker. This work improved system scalability by 40% and accelerated deployment cycles by 60%.

Developed and optimized high-traffic RESTful APIs and GraphQL endpoints serving more than 50,000 monthly active users. Reduced average API response time by 55% through caching and query optimization, and implemented Redis caching and Pub/Sub messaging to reduce database load and support real-time service events.

Machine Learning Engineer iCog Labs

Evaluated and debugged MOSES symbolic program-synthesis implementations in MeTTa, identifying logical gaps and improving the correctness of AI-generated outputs.

Built and optimized a tree-based evaluator for binary expressions to improve execution accuracy and performance. Refactored Python codebases to improve modularity, readability, maintainability, and clean-code practices in a production AI research environment.

Applied AI & Machine Learning Resident gheero

Built end-to-end machine learning pipelines covering data preparation, feature engineering, model development, evaluation, and optimization. Developed predictive models for task overdue risk, trainee-to-job matching, and dynamic task distribution.

Explored inference cost-reduction methods for RAG pipelines, including context budgeting and retrieval optimization. Applied model evaluation, hyperparameter optimization, leakage prevention, and time-aware validation to improve model reliability.

Education

Learning history

HiLCoE School of Computer Science and Technology

Bachelor of Software Engineering, Software Engineering

Cumulative GPA: 3.8/4. Relevant coursework included UNIX, Windows Programming, Database Management, MSSQL, .NET Programming, Object-Oriented Programming, Data Structures and Algorithms, and Web Technologies.

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