Machine Learning Experts in Vienna
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Meet FRATCH Experts in Vienna, who have recently used Machine Learning
Stefan Dangubic
Last position:
BI Consultant in Controlling at Reutter GmbH
- Extraction, transformation, and cleansing of data from Microsoft Dynamics AX
- Creation of sales reports in Power BI
- Training employees in business intelligence
- Technologies: Power BI, SQL, SQL Server Integration Services (SSIS)
Marcel Steger
Last position:
Senior AI Engineer - Python at Insurance Company
Project Tech Stack: Python, AWS, Azure, FastAPI, openai, pandas, unittest/pymock
Achievements:
- Engineered automated data extraction pipelines to transform complex Excel datasets into structured formats via LLM-driven workflows.
- Architected a generative slide-deck engine that translates natural language prompts into formatted presentation assets.
- Integrated advanced LLM capabilities with the OpenAI Response API, implementing sophisticated tool-calling and structured output logic.
- Developed and containerized scalable backend microservice using FastAPI, Docker, and OpenShift to host and serve agentic skills.
Fabio Galvagni
Last position:
IT Architect, Requirements Analyst and Consultant at CANCOM
- Supports CANCOM customers in migrating legacy on-prem systems to Microsoft Fabric and Microsoft Foundry
- Takes over and stabilizes existing solutions after a short handover
- Business analysis and requirements engineering for migration to a new cloud environment
- Optimization of machine learning models for feature extraction and customer profiling
- Ensures data protection and compliance
- Leads the migration of on-prem systems to Microsoft Fabric
- Designs new AI platforms for clients
- Tests the integration of chatbots for document intelligence with Microsoft Foundry, including requirements analysis, implementation, validation, and client communication
Thomas Becker
Last position:
Agile Coach, Scrum-Master at ÖBB (Infra)
- Challenge: poor project results and team performance, very poor work environment
- Solution: introduction of agile planning processes, teaching agile principles within the SAFe framework
- Innovation: consistent use of agile methods; introduction of requirements engineering, story writing
- Leadership: interface with the board, program management Opel Europe, GM USA and international markets
- Result: most productive team in the ART; increased planning accuracy to over 85%
- Team size: 10
Lorenz Graiff
Last position:
Business Analyst at Wirtschaftsagentur Wien
- Conducting a feasibility study on introducing an in-house DWH as a central data source
- Conducting workshops for current state analysis (processes, reports, KPIs) together with the clients
- Gathering and detailing business requirements including a target concept for an in-house DWH
- Coordinating and clarifying data deliveries and interfaces in meetings with stakeholders and data providers
- Developing initial data models as a basis for data quality and later implementation
- Drafting solution variants including architecture and operation options and decision basis
- Creating the business case including effort estimates, cost-benefit analysis, and decision report
Maximilian Götz-Mikus
Last position:
Solo Developer / Founder at InvAPI
- Privacy-first, stateless e-invoice API providing AI-powered extraction, bidirectional format conversion (UBL/CII/ZUGFeRD), batch processing, and validation for German/Austrian e-invoice compliance
- Technologies: Nuxt 4, Vue 3, Nitro, TypeScript, Cloudflare (D1, R2), Stripe, OAuth, AI/LLM integration
Dániel Németh
Last position:
Postdoctoral Researcher - Theoretical and Computational Physics at Radboud University
- Built and maintained C and C++ simulation engines with Python analysis for studies of 4D random geometries on shared HPC systems.
- Developed modular Python pipelines with clear interfaces and caching for large datasets to improve analysis throughput and reuse.
- Automated SLURM and PBS batch workflows for submission, monitoring, environment capture, and artifact packaging to ensure reproducibility.
- Refactored utilities into tested, documented packages to lower maintenance effort and support collaboration.
- Supervised BSc students and organized seminars.
- Published several peer-reviewed papers.
Kevin Lang
Last position:
Data Consultant at VBV Pension and Provident Fund Austria
Development of a structured framework and comprehensive guidelines for documenting business and audit processes in a regulated financial environment. Support for the standardization of process documentation to improve transparency, consistency, and traceability across all operational workflows. Contribution to defining documentation standards, templates, and governance principles for internal process management and audit readiness.
Atif Yilmaz
Last position:
Head of Technology at Quadrobotics R&D and Software Development Inc.
- Integrated cutting-edge software and hardware enhancements into quadruped robotic systems
- BARS Robotic Dog Platform: computer boards integrations, data link integrations, LTE, anti-jam datalink, RF datalink, satcom datalink integrations, GNSS integrations, GNSS-RTK integration, payload integrations, RCWS (5.56, 7.62 remote control weapon station integration), CBRN sensor integrations (chemical)
- AYBARS Robotic Dog Platform: computer boards integrations, data link integrations, LTE, anti-jam datalink, RF datalink, satcom datalink integrations, GNSS integrations, GNSS-RTK integration, payload integrations, RCWS (9 mm remote controlled gun-box integration), CBRN sensor integrations (chemical)
Robert Prazak
Last position:
Editorial Lead, Falstaff International Online at Falstaff Verlag
Discover over 15,000 top freelancers
Statistics of experts using Machine Learning
Aggregated from the professional profiles of matched freelancers.
Experience
15 years
Position duration
3 years
Positions per freelancer
8
Top business areas
Information Technology, Business Intelligence, Project Management
Top industries
Information Technology, Banking and Finance, Media and Entertainment
Certification focus areas
Business Intelligence, Information Technology, Project Management
Bachelor's degree or higher
88%
Master's degree or higher
88%
Doctorate
25%
Certifications per freelancer
2
Most common languages
German, English, French
Speak two or more languages
90%
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Vienna are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Vienna using Machine Learning
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it is
Machine learning is a way to build systems that learn patterns from data and improve on a task without fixed rules for every case. Teams use it for prediction, ranking, classification, forecasting, and language or image understanding. Strong work starts with clear data, a clear target, and a practical success measure.
Typical work
- Build churn, demand, fraud, or risk models
- Create recommendation and search ranking logic
- Classify text, images, tickets, or documents
- Prepare features, training data, and evaluation sets
- Support inference, monitoring, and retraining
Tooling
Most projects use Python, NumPy, pandas, scikit-learn, TensorFlow, or PyTorch. For production, experts also work with SQL, MLflow, Docker, APIs, and cloud services such as AWS, Azure, or Google Cloud. The right stack depends on whether the goal is fast prototyping, batch scoring, or live inference.
When to hire
Companies bring in freelance machine learning specialists when a product team needs a model built quickly, an existing model underperforms, or internal staff need extra depth. In Vienna, this often fits firms in finance, mobility, logistics, health, and industrial software. Remote collaboration works well, as long as data access, review steps, and business context are clear.
Strong profiles
Strong professionals do more than train a model. They question the data, set baselines, explain trade-offs, and make results usable in real systems. They write clean, reproducible work, know how to avoid leakage, and can discuss why one approach beats another for the business goal.
Delivery focus
A good engagement ends with something a team can run, review, and maintain. That can be a notebook, a trained model, a scoring service, an evaluation report, or a full pipeline. For Vienna-based teams, bilingual communication may help, but the core need is the same: clear outputs, stable handover, and measurable behavior.
Frequently asked questions
Not sure where to start with Machine Learning? These answers cover the essentials.
Machine Learning is used to turn data into predictions or decisions. Companies use it for forecasting, anomaly detection, recommendations, document sorting, search ranking, and language understanding. The best projects start with one narrow business problem, not a vague wish for “AI.”
Machine Learning learns patterns from examples, while rule-based automation follows instructions written by people. That matters when the inputs are messy, changing, or too complex for fixed rules. If the logic is stable and easy to describe, traditional software may be the better fit.
A strong Machine Learning specialist usually works comfortably with Python, SQL, data cleaning, and model evaluation. For production work, skills in APIs, Docker, cloud services, and monitoring are useful too. For text and language tasks, NLP knowledge is often important.
Machine Learning work goes faster when the goal, input data, and success metric are already defined. A freelancer can help shape the problem, but they should not have to guess which outcome matters. Even a rough baseline dataset and sample cases make the first phase much stronger.
Machine Learning work is often remote-friendly because much of it happens in code, notebooks, and review sessions. In Vienna, on-site time can still help when sensitive data, stakeholder workshops, or access constraints are involved. Many teams use a mixed setup.
The right Machine Learning stack depends on the task. scikit-learn is common for classical modeling, while TensorFlow and PyTorch are often used for deep learning and more custom workflows. A good freelancer chooses tools that fit the problem, not the other way around.
Look for clear thinking, not just model names. A strong Machine Learning professional can explain data quality, baseline results, validation setup, and failure modes in plain language. Good signs are reproducible work, honest trade-offs, and a practical handover plan.
Machine Learning projects often include messy data, changing requirements, and a need to communicate clearly with non-specialists. Freelancers should expect to document assumptions, validate results carefully, and support handover to the team. The best engagements are those where business context is available early.
The average hourly rate of freelancers in Vienna, Austria who have used Machine Learning in their recent projects is 96 €, which corresponds to a daily rate of about 771 € based on an 8-hour working day.
Of the freelancers in Vienna, Austria who have used Machine Learning in their recent projects, 88% hold at least a Bachelor's degree, 88% hold at least a Master's degree, and 25% hold a doctorate.
On average, freelancers in Vienna, Austria who have used Machine Learning in their recent projects have 15 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers in Vienna, Austria who have used Machine Learning in their recent projects are German (90%), English (90%), and French (30%).
The most common industries among freelancers in Vienna, Austria who have used Machine Learning in their recent projects are Information Technology (60%), Banking and Finance (50%), and Media and Entertainment (40%).
The most common business areas among freelancers in Vienna, Austria who have used Machine Learning in their recent projects are Information Technology (90%), Business Intelligence (70%), and Project Management (70%).
Main locations of FRATCH Experts, who have recently used Machine Learning
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Countries:
Vienna 
Graz Request a free demo
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Philipp Thomaschewski
FRATCH CEO
