📍 Athens, Greece · AI Engineer @ Metlen Energy & Metals
AI-native engineer with an MSc in Applied Machine Learning from Imperial College London (Merit). Production experience deploying ML systems on Azure, AWS, and GCP across energy, education, and telecommunications. R&D focus on agentic workflows and LLM-based assistants. Master's thesis: Large Language Models for data compression.🔭 Recent Experience:
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Metlen Energy & Metals — AI Engineer (Apr 2025–present): Building clustering algorithms for energy profiling and annual consumption prediction for 500+ new smart-meter customers monthly, plus a look-alike pricing model in Azure ML for customers without historical data. Leading R&D on generative AI and agentic architectures.
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Faculty AI (Department for Education): Authored ADRs and built FastAPI endpoints for the DfE Content Store assessment-data API on Azure; provisioned IaC with Terraform + Azure DevOps, cutting deployment time by ~15 hours per iteration. Built a Dash dashboard prototype demoed to EdTech developers at a sponsored hackathon.
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Imperial College London — MSc Applied Machine Learning (Merit): Thesis on Large Language Models for data compression. Scholarship recipient (EUROTANKERS INC and Union of Greek Shipowners).
🚀 Currently Building:
- Agentic workflows and LLM-based assistants — prototyping intelligent assistants and automated reasoning pipelines around LangChain, Google ADK, and Hugging Face Transformers.
- Production ML on Azure ML — clustering and look-alike pricing for energy customers, with SQL + Python pipelines.