Production-Ready AI · Remote Worldwide · Vienna (CET)
AI that impresses your customers and sets you apart from the competition.
I build production-ready AI for B2B SaaS: reliable so your customers can depend on it, and efficient enough to cut running AI costs by up to 99%. 12+ years of production ML experience — long before the LLM hype.
About
Your technical partner for AI —
from idea to launch.
I’m a senior engineer who has been building machine learning & AI models for over a decade. As a former startup CTO, I understand both technology and business, and I build AI tailored to solve your business case.
From architecture and model selection to test strategy: I explain every option clearly, in plain language and without jargon. You get a product that matches your vision, sets you clearly apart from the competition, and impresses customers.
Languages
- German
- English
Location
- Vienna, Austria (CET)
- Remote worldwide
Education
- WU Vienna — MSc Quantitative Finance
- TU Vienna — MSc Business Informatics
Services
Main offering & more
Main offering
Production-Ready AI
I design and build AI features and products that impress your customers and set your company apart from the competition.
Put new AI models to work
I show you what modern AI models make possible today and turn that into products and features that didn’t exist before.
Build exactly what you envision
You have a clear plan — I implement it and build your AI feature or product. LLM-based or classic ML.
Get finished prototypes across the line
Reduce hallucinations, optimize latency, stabilize outputs. Users should be able to rely on your product 100%.
Optimize inference cost and latency
Caching, routing, model selection and batching to cut 30–70% of running costs. Hybrid LLM solutions for up to 99% reduced costs.
Stack
The tools I use to build and run production-ready AI features.
Languages
ML & AI
Data
Infrastructure
Also experienced with: R · PHP · C++ · Go · Aerospike · Redis · Kafka · Hadoop · Hive · GraphQL · Next.js · React · Node.js
Projects
Selected projects
PAXLY — packaging procurement platform
ML-based packaging optimization saving e-commerce companies like Flaconi 10–15% on daily shipping costs. Co-founded in 2016 and, as CTO until 2023, built the entire product from scratch. Closed two funding rounds totalling over €1M. Engineered so robustly that critical hotfixes dropped from one or two a month to about one a year.
10–15% shipping cost saved · ~1 hotfix/year · €1M+ funding
paxly.ai More on fractional CTO
Firmbase — company search engine for the UK market
Company search engine for the UK market with 5.5M+ records, built full-stack. A crawling pipeline captures ~100,000 pages per day per machine; AI-powered data enrichment end-to-end. Result: ~80% relevant matches per search vs ~20% with common tools — roughly 5× more precise lead lists.
~5× more precise matches · 5.5M companies
firmbase.co
Relevant AI work
AI & ML in production — for clients
Selected AI and ML projects with measurable impact. I’m happy to name the clients in a call.
Regulated Medical Software
For large customers, core features were so slow they were effectively unusable — users assumed they were broken. Optimized algorithms, caching and optimized database queries brought them back to life: up to 90% faster load times. Plus an AI assistant with intent classification: 95% fewer wrong answers — built to the V-model.
95% fewer wrong answers · up to 90% faster load times
TypeScript · Node.js · PostgreSQL · LLM
AdTech · Real-Time Advertising
Regression-tree model for floor-price optimization in real-time ad auctions: around +8% revenue, in the millions. Plus a data pipeline with an 80% smaller data warehouse and 75% less reporting load.
≈ +8% revenue · −80% data volume
Java · C++ · Spark · ML
Audit Data · Food Safety
Explainable anomaly detection for audit data: every flag comes with a full reasoning chain — the system tells you not just that something is unusual, but why. Decisions stay traceable and defensible for auditors.
Full reasoning chain · no black box
Python · PGM · Neural Nets
Climate-Tech · Data Pipeline
A pipeline ran documents through an expensive LLM — at millions of documents, cost explodes. Instead of naively filtering with the LLM, the LLM trains a cheap TF-IDF model that filters upfront: only ~10,000 of 3M documents reach the expensive stage. LLM costs cut by ~99%.
≈ −99% LLM cost
Python · AWS · Ray · LLM
Testimonials
What my clients say
„Alex redesigned our data pipeline and cut the data volume by 75% — with no loss in insight. Fast, rock-solid, and always reachable when it mattered.“
Julia Wagner
Co-founder & COO, UNOMR„Alex took our marketplace platform from zero to fully operational in just 8 weeks. It’s what made our growth and fast scaling possible.“
Sabine Niedermüller
Managing Director, HeldYnProcess
How I work
Intro call
Understand your problem
A short, no-obligation call to understand your project and your goals. No weeks of analysis. We clarify the key questions directly. Free of charge.
Delivery
Fast and reliable
Focused sprints (1–4 weeks), regular updates and tested code. You always see where we stand and have a say in every decision.
Handover
A clean finish
Documentation, knowledge transfer and a product that runs without me. No lock-in, no hidden dependencies.
Investment
from €150
Hourly rate
€1,200 – 1,500
Day rate for project work
Precise estimate after a free intro call.
Contact
Let’s talk about your use case.
Whether you want to bring an AI feature into production, take a prototype live, or first figure out what’s technically feasible — a short call is enough to work out how I can help.
Currently available for new projects
Book a free intro call