Matej Kalc · Portfolio
Full-Stack AI Engineer. Ideas into products.
I’m based in Trieste, engineering AI at NLB (opens in new tab) and founding Timeo (opens in new tab). I balance model quality, latency, and cost under real business constraints.
- RAG and evaluation
- Agent orchestration
- LangGraph workflows
- LLMOps for GenAI
Flagship work
Products and applied ML systems, shown through live interfaces and published technical work.
Timeo
2025Scheduling SaaS for independent restaurants and cafés: bring availability and coverage together, generate a draft, and review it before sharing.
Outcome
Pilot users reduced schedule planning from about 3 hours to around 20 minutes.
- Optimization
- Product
- Operations AI
Automobile Insurance Fraud Detection
2024Heterogeneous graph neural network pipeline over claims, customers, and provider relationships.
Outcome
A hybrid HGFD + XGBoost model improved precision by 17.4% over the XGBoost baseline in a business-unit study.
- Graph Neural Networks
- PyTorch Geometric
- Insurance ML
Spiaggia Oggi
2026Nationwide Italian beach discovery guide for finding and comparing named destinations with visible source provenance.
Outcome
Published 1,128 named destinations across 15 coastal regions while keeping missing information and source limitations explicit.
- Next.js
- PostgreSQL
- Geospatial Data
Timeline
2025 - present
Full-Stack AI Engineer
NLB d.d., Ljubljana (opens in new tab)
- Led a student team building an agentic document-validation system with orchestration and validation checkpoints, estimated to reduce manual work by 1,000+ hours per year.
- Shipped an AI report generator with web search, retrieval-augmented generation, and image generation.
- Built dynamic graph neural networks for anti-money-laundering monitoring in banking workflows.
2025 - present
Founder
Timeo (timeo.matejkalc.com) (opens in new tab)
- Built and launched Timeo, a scheduling SaaS for independent restaurants and cafés.
- For pilot users, schedule preparation dropped from about 3 hours to around 20 minutes.
2024 - 2025
Data Scientist
Zurich Insurance Group, Ljubljana (opens in new tab)
- Developed graph ML for automobile fraud detection; a hybrid model improved precision by 17.4% over the XGBoost baseline in a business-unit study.
- Developed Databricks workflows that reduced batch inference time by 75%.
2023 - 2024
Data Scientist (Student)
Medius.si d.o.o., Ljubljana (opens in new tab)
- Created a PyTorch package for one-day-ahead solar power production forecasting with recurrent neural networks.
More work
Earlier products and applied machine-learning projects spanning geospatial data, forecasting, and large-scale modeling.
Atlante Casa Trieste
2026Interactive map of Trieste real-estate values with OMI zone ranges and local market filters.
Outcome
Turned public valuation data into a clearer browsing experience for exploring price differences across the city.
- Next.js
- Interactive Maps
- Real Estate Data
Traffic Prediction with Temporal GNNs
2023Sensor-graph forecasting model for highway traffic prediction several hours ahead.
Outcome
Built an open-source spatiotemporal GNN implementation and technical report as part of a four-person team.
- Temporal GNN
- Time Series
- Spatial Data
CTR Prediction at Scale
2021Compared neural and factorization models for click-through-rate prediction on Outbrain data.
Outcome
Built and tuned multiple model families with Bayesian optimization on HPC resources.
- CTR Modeling
- Deep Learning
- Bayesian Tuning
About
I build end-to-end AI products for production use, from orchestration and evaluation on the backend to usable frontend experiences. In regulated environments, I prioritize observability and reliability. In products, I focus on user value and iteration speed.
- Core stack
- TypeScript · Next.js · Python · FastAPI · PostgreSQL
- Modeling
- RAG · Agent Orchestration · LangGraph Workflows · LLM Evaluation · Tool-Using AI Systems
Education
- MSc in Data Science, Faculty of Computer and Information Science, University of Ljubljana (GPA 9.0)
- BSc in Computer Science, Faculty of Computer and Information Science, University of Ljubljana (GPA 9.1)
Achievements
- 1st place - IEDC Case Study Competition (NLB team, advancing to international round) (opens in new tab)
- 1st place - Data Science Hackathon (Etrel, EV charging clustering)
- 1st place - NLP word sense disambiguation with SloBERTa (opens in new tab)
- 3rd place - Data Science Project Competition (2021 and 2022) (opens in new tab)
Let’s talk
I’m open to selected AI engineering roles and product collaborations where reliable systems, measurable outcomes, and thoughtful delivery matter.
Trieste, Italy