Also: Taras builds AI systems

The technical side of Taras

Before the mountains and the coaching, there's a technical career: four-plus years building AI products, mostly LLM and NLP systems that go from idea to something a real business actually runs. If you need that side of me for your team, here's the work.

Experience

01

ML Engineer · Litslink

Sep 2023 – Present
  • Built an LLM-powered food-ordering chatbot (Flowise, Supabase, LangSmith), containerized and shipped with Docker and CI/CD.
  • Trained a PyTorch company-classification model at 85% accuracy on a custom dataset collected via web scraping.
  • Built a Slack AI assistant (FastAPI, MongoDB, Mistral API) that filters high-volume channels down to what actually matters.
02

NLP Engineer · HOLYWATER

Sep – Dec 2024
  • Developed a proof-of-concept RAG pipeline for semantic book evaluation using custom Hugging Face datasets and embedding-based ranking.
03

ML Engineer · MindCraft.ai

Mar – Aug 2023
  • Designed TensorFlow housing-price models: 9% MAPE for sellers, 3% MAPE for buyers.
  • Built an end-to-end PostgreSQL data pipeline with automated cleaning and feature engineering.
04

ML / Deep Learning Researcher · NYU & Stony Brook University

Jun 2022 – Aug 2023
  • Responsible AI, NYU — studied how null-value imputation affects fairness and performance in ML decision systems.
  • Stony Brook University — predicted 3D protein structure from amino acid sequence using PyTorch.

Education & writing

Bachelor of IT and Business Analysis, Ukrainian Catholic University (2020–2024). Taught Python statistics seminars as an Econometrics TA. Thesis on vocal extraction in low-data regimes — paper, repo, demo.

Writes public notes on technical books: High Performance Python, Learning Bash Shell, Learning Unix.

Need an AI engineer, not a mountain guide?

Happy to talk through a project, a build, or a consulting engagement.