Tsegay Assefa
Junior Machine Learning Engineer
Building production-ready AI systems with 85%+ accuracy. Specializing in RAG architectures, Bayesian time-series, and MLOps.
Building production-ready AI systems with 85%+ accuracy. Specializing in RAG architectures, Bayesian time-series, and MLOps.
Junior Machine Learning Engineer with hands-on experience building production-ready AI systems including RAG chatbots, time-series anomaly detection models, and ETL data pipelines. Skilled in Python, FastAPI, PostgreSQL, and Docker. Experienced in maintaining reliable ML systems and backend services.
PyMC • Bayesian Stats • React • Flask
Implemented Bayesian change point detection models to identify regime shifts in oil prices. Achieved 99.47% confidence in detecting structural breaks and quantified +31.8% price impact.
LangChain • FAISS • FastAPI • Docker
Production-ready retrieval-augmented generation system for financial complaint analysis. Integrated LLM with vector database for contextual responses.
PostgreSQL • dbt • FastAPI • Docker
End-to-end healthcare data pipeline processing 50k+ messages from Telegram channels. Automated ETL workflow with analytics dashboard.
2023 – 2027 (Expected)
Specialization: Data-Centric Computing & Software Engineering
2025 – 2026
Final Score: 99.7%
10+ industry-level ML/AI projects including RAG systems, forecasting models, and Bayesian analysis.
2025
Final Score: 97%
Network security monitoring, system reliability, infrastructure defense.