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I'm Tinsae Abreham, a machine learning engineer with over seven years of experience and a background in electromechanical engineering. I specialize in Generative AI (RAG, LLMs), graph-based systems, and distributed AI frameworks, and I enjoy building complex transformer architectures from scratch while minimizing inference latency in decentralized environments. I bridge hardware automation and advanced neural architectures, collaborating across teams to turn data into actionable insights and delivering robust, scalable solutions for industry and research. I’m passionate about turning cutting-edge ideas into tangible outcomes that move the needle for organizations and communities.…I'm Tinsae Abreham, a machine learning engineer with over seven years of experience and a background in electromechanical engineering. I specialize in Generative AI (RAG, LLMs), graph-based systems, and distributed AI frameworks, and I enjoy building complex transformer architectures from scratch while minimizing inference latency in decentralized environments. I bridge hardware automation and advanced neural architectures, collaborating across teams to turn data into actionable insights and delivering robust, scalable solutions for industry and research. I’m passionate about turning cutting-edge ideas into tangible outcomes that move the needle for organizations and communities.

Tinsae Abreham

AI Engineer, Data Scientist, Full Stack Developer, +3

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I'm Tinsae Abreham, a machine learning engineer with over seven years of experience and a background in electromechanical engineering. I specialize in Generative AI (RAG, LLMs), graph-based systems, and distributed AI frameworks, and I enjoy building complex transformer architectures from scratch while minimizing inference latency in decentralized environments. I bridge hardware automation and advanced neural architectures, collaborating across teams to turn data into actionable insights and delivering robust, scalable solutions for industry and research. I’m passionate about turning cutting-edge ideas into tangible outcomes that move the needle for organizations and communities.…I'm Tinsae Abreham, a machine learning engineer with over seven years of experience and a background in electromechanical engineering. I specialize in Generative AI (RAG, LLMs), graph-based systems, and distributed AI frameworks, and I enjoy building complex transformer architectures from scratch while minimizing inference latency in decentralized environments. I bridge hardware automation and advanced neural architectures, collaborating across teams to turn data into actionable insights and delivering robust, scalable solutions for industry and research. I’m passionate about turning cutting-edge ideas into tangible outcomes that move the needle for organizations and communities.

Available to hire

I’m Tinsae Abreham, a machine learning engineer with over seven years of experience and a background in electromechanical engineering. I specialize in Generative AI (RAG, LLMs), graph-based systems, and distributed AI frameworks, and I enjoy building complex transformer architectures from scratch while minimizing inference latency in decentralized environments.

I bridge hardware automation and advanced neural architectures, collaborating across teams to turn data into actionable insights and delivering robust, scalable solutions for industry and research. I’m passionate about turning cutting-edge ideas into tangible outcomes that move the needle for organizations and communities.

Skills

Experience Level

Expert

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Expert

Expert

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Expert

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Expert

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Expert

Language

English

Advanced

Work Experience

AI Engineer Researcher at iCog_Labs

May 22, 2025 - June 10, 2026

Pattern mining algorithms Distributed AI and Singularity Hyperon MeTTa optimization Knowledge graphs Python, Distributed Systems

AI Engineer Researcher at iCog Labs

May 1, 2025 - Present

Engineered pattern mining algorithms within the Singularity Hyperon framework, increasing data processing throughput by 30% to enhance knowledge representation for decentralized AI. Accelerated inference workflows for the MeTTa language, reducing execution time by 40% for recursive AGI research modules. Collaborated on cross-functional teams to integrate pattern miner logic with large-scale knowledge graphs, slashing query latency by 15% in production simulations.

Automation Engineer at ROBOX

January 1, 2024 - May 1, 2025

Spearheaded control logic design for CNC machinery, integrating custom firmware that improved manufacturing precision to within 0.05mm tolerance. Streamlined machine design workflows using modular components, cutting the design-to-prototype cycle by 20% and saving 15+ engineering hours monthly. Deployed automated Shell scripts for system diagnostics, achieving 99.9% uptime for CNC operating parameters during critical production runs.

Automation Engineer (Freelance) at Upwork (Freelance)

March 1, 2023 - December 1, 2023

Designed and deployed multi-agent AI systems utilizing LangChain and LangGraph to automate B2B customer support, content generation, and administrative workflows. Integrated autonomous LLM agents with client CRMs and external APIs, reducing manual data processing time by 65% across 5+ international SMBs. Built and fine-tuned custom RAG pipelines with vector databases (Pinecone, ChromaDB) to ground agent responses in proprietary company data with high accuracy.

Remote Agentic AI Automation Engineer at Upwork (Freelance)

March 1, 2023 - December 1, 2023

Data Science Intern at ZayRide

August 1, 2022 - February 1, 2023

Developed automated data pipelines using Python and SQL to extract and clean ride-hailing data, preparing large datasets for machine learning models. Trained XGBoost and Random Forest models to predict peak ride demand periods, improving driver allocation efficiency by 15%. Created interactive Power BI dashboards to visualize weekly performance and geospatial metrics for the operations team.

Embedded Systems Developer at AASTU Robotics Innovation Lab

October 1, 2020 - July 1, 2022

Programmed microcontrollers (Arduino, ESP32) using C/C++ for autonomous navigation robots, integrating sensor data for real-time obstacle avoidance. Built a real-time data logging system via Serial communication and Python scripts to monitor hardware performance during testing phases. Collaborated with a team of 4 engineers to prototype an automated sorting arm, winning 2nd place in a university-wide tech competition.