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Paul Iusztin · @pauliusztin

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From linkedin.com/in/pauliusztin

I am an AI Engineer, author, and educator based in Timișoara, Romania. Over more than a decade I have shipped 20 applications, written the Amazon bestseller LLM Engineer’s Handbook, run Decoding AI Magazine for a 160 k‑plus audience, and taught the Agent Engineering course at Towards AI. My career has focused on end‑to‑end AI product development, from data collection through production deployment, monitoring, and evaluation.

  • Senior ML Engineer at BRAHMA AI (Jan 2024 – Sep 2024): reduced data‑curation latency by ‑88.7 % and batch‑pipeline processing time by ‑62.5 %, while cutting AWS cost by ‑52 %.
  • Senior ML Engineer at BRAHMA AI (May 2023 – Dec 2023): achieved a ‑62.5 % reduction in batch‑pipeline time and a ‑52 % reduction in AWS spend.
  • ML Tech Lead at CoreAI (Dec 2022 – Jun 2023): built a real‑time recommender serving > 100 k users via Kafka Streams, Kotlin, and PyTorch.
  • Founder/Member, Technical Staff – Decoding AI Magazine (Jun 2023 – Present): scaled RAG ingestion from 1 500 to > 36 000 documents per hour.
  • Senior ML Engineer at Everseen (Aug 2021 – Feb 2022): achieved mAP 85 % on 100 k retail images and a ‑50 % inference speed‑up using Docker + ONNX + TensorRT.
  • Junior ML Researcher at Continental (Nov 2019 – Oct 2020): reduced model memory usage by ‑40 % through Dynamic Voxelization.
  • Senior Software Engineer at Dorel (2022 – Present): introduced a unit‑test suite that decreased development time by 20 %.
  • Master’s dissertation in ML: reinforcement‑learning order‑execution algorithm realized a 2.8 % monthly compound interest on average.

My decisions consistently favor infrastructure‑as‑code, CI/CD, monitoring, and experiment tracking to improve latency, cost, and developer productivity across all projects.