Mateusz Jakubczak
Pragmatic AI Engineer bridging the gap between technical complexity and business value.
Profile
Pragmatic AI Engineer with a dual background in Computer Science and Economics. Combines the rigor of Goldman Sachs with startup agility to deliver secure, scalable, and ROI‑focused AI architectures.
Technical Skills
- Cloud & MLOps: GCP, AWS, Docker, Kubernetes, Terraform, CI/CD, ETL, Model Deployment
- AI/ML: Pandas, NumPy, scikit‑learn, PyTorch, FastAPI, LangChain/LangGraph, LLMs, Vector DBs
- LangOps: RAG, prompt/context engineering, LangFuse, Milvus/pgvector
- Languages & DBs: Python (Expert), Java (Proficient), SQL, MongoDB
Experience
- Quickchat.ai — ML Engineer: Multi‑tenant LLM platform; advanced RAG; GCP migration with Terraform & CI/CD; TDD culture.
- Goldman Sachs — Analyst: High‑throughput market data platform; k8s private cloud migration; data quality monitoring; automation.
Projects & Highlights
Invited Speaker — Foundation Conf 2025
We tested DeepSeek — trade‑offs between model quality, speed, and infra cost.
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Supervision Hack 2023 — 2nd
Financial Stability Monitoring Tool (KNF): scraping + NLP + anomaly detection.
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Supervision Hack 2022 — 1st
Automated Risk Classification from financial documents (OCR + CV).
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KGHM Copper Smelter — Production
Winning AI control system deployed to stabilize and optimize primary smelting.
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Books & Reading
Coming soon — a short list of books that influenced my approach to AI, systems, and economics.