Machine Learning Experts in Austria
in minutes from over 15,000 CVs with the power of AIHire experts who build ML models, refine data pipelines, and ship prediction systems with Python, scikit-learn, TensorFlow, and PyTorch. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Austria, 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
Mario Tuta
Last position:
External Lecturer at FH Kufstein Tirol – University of Applied Sciences
- Study: Data Science & Intelligent Analytics
- Module: Big Data Processing
Thomas Becker
Last position:
Agile Coach, Scrum-Master at Ă–BB (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
Namik Delilovic
Last position:
Test Manager / Test Automation Engineer at Sky Deutschland GmbH
- Implemented and maintained 443 automated test cases with a 99% pass rate (441/443)
- Enabled CI for test automation: automated runs on review/merge, reporting via Xray
- Introduced accessibility and performance checks and established them in reporting
- Served as QA lead in daily operations with stand-ups, Kanban progress tracking, prioritization, and targeted task distribution
- Handled defect triage and stakeholder communication with daily triage, QA status analysis, and actionable recommendations
- Developed and maintained a stable regression suite for CRM/Salesforce flows (UI/E2E and near-API validations)
- Integrated CI/CD using Jenkins pipelines with Groovy (IaC)
- Maintained QA documentation, test conventions, and processes in Confluence, aligned across the team
- Conducted Salesforce Einstein chatbot testing with intent/topic validation and output checks, and used Robot Framework/Python suites for continuous quality monitoring
- Technology stack: Jira, Xray, Confluence, Jenkins, Groovy, Git, Java, Selenium, Playwright, Cucumber, TypeScript, Postman, REST, Salesforce, Google Cloud, Lighthouse, Evinced, Scrum/Kanban, BDD (Gherkin)
Nikolaus Jäger-Grassl
Last position:
Integration Architect at CECIL
Designed an API-first omnichannel integration, linking WhatsApp Business API with Salesforce Marketing Cloud to unify customer data across multiple platforms.
Automated customer onboarding and engagement workflows using Marketing Cloud Journeys, SSJS, and Azure Functions.
Developed a middleware layer to sync WhatsApp interactions with Sales Cloud for seamless customer experience tracking.
Georg Oberdammer
Last position:
CIO / CDO at TroGroup
- Design and execution of the transformation journey of IT & digitization and enablement of the further development of the group
- Development of the global IT & digitization strategy (motto: “ahead of the wave”) based on group standards and USP-driven digital solutions
- Definition of the digital strategy as part of the company’s 2030 strategy with a focus on the value disciplines “operational excellence,” “customer intimacy,” “product leadership”
- Design and implementation of a business-focused, global IT organization, including existing shadow IT parts
- Digital product development with a focus on IoT, data science, AI, software development (DevOps), cloud architecture, and Azure cloud services
- Initiation and ramp-up of the CoE for artificial intelligence and data analytics, including several agentic AI projects
- Definition and global rollout of the enterprise, infrastructure, and application architecture
- Cloud transformation including setup and execution of the global S/4HANA rollout, introducing new capabilities and modules
- Global business process standardization, automation, and end-to-end digitization within and across divisions
- IT/OT integration (shop floor, CAx integration)
- P&L responsibility and further development of digital marketing & sales channels, SEO/SEA, online product configuration, PIM/DAM, eBusiness/eCommerce systems
- Implementation of a global intranet portal and several digital solutions like Workday, Concur, Softconcis, Tacto, xFlow
- Further development of Salesforce beyond CRM into a sales backbone
- Support of M&A and divestiture
- Cyber security excellence, data protection, and NIS2 preparation
- Ramp-up of nearshore and offshore locations (Poland, India)
- Evaluation and implementation of business-value–driven IT innovation like RPA, business process AI, and low-code
- IT budgeting and controlling, KPI reporting, and negotiation of large IT contracts
- Global recruiting, people retention, and development
- Stakeholder management with executive management and heads of divisions
Armin Fanzott
Last position:
Head of AI & Data Science at Ascent DACH
- Lead architect for AI and ML projects including GenAI, LLM-based apps and forecasting solutions
- Guided customers through solution scoping, architecture design, and PoCs across various industries (Pharma, Insurance, Logistics, FMCG)
- Delivered production ML pipelines using Azure ML, MLflow, and MLOps best practices
- Responsible for effort estimation, delivery and staffing of 5 – 10 projects simultaneously
- Hiring manager for the data science and AI team and responsible for creating the technological offering and roadmap in the AI & Data Science space
- Built and scaled the AI/Data Science service offering from scratch to a high 6-figure annual revenue with 30+ successful deliveries and 20+ clients
- Regular speaker at AI and data science conferences and academic institutions
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.
Maximilian Aster
Last position:
Technical Project Lead / Solution Architect at UNIQA Insurance Group
- Planning, monitoring, coordination, and documentation of the output project as part of the policy migration to the UNIQA Insurance Platform.
- Planning and design of new requirements.
- Designing a consistent, maintainable, and scalable application architecture.
Michael Selinger
Last position:
Director, IT at Austria Juice GmbH
- Directed IT operations across 13 sites in China, Romania, Poland, Hungary, Germany, Ukraine, and Austria.
- Built and led a new IT team with personnel based in Poland, Hungary, Romania, and Germany.
- Upgraded outdated IT infrastructure at sites in Austria, Germany, Romania, and Poland, enhancing clients, printers, networks, servers, storage, firewalls, and backups.
- Retired the legacy phone system and transitioned to Teams.
- Established and deployed AI tools, including Copilot and Zapier.
- Implemented NIS II readiness and achieved ISO 27001 certification.
- Eliminated inefficient business applications to enhance operational efficiency.
- Developed and executed new processes for operations technology, business process outsourcing, purchasing, human resources, and IT.
- Launched a new SAP Warehouse System.
- Established IT standards across all sites.
- Engaged effectively with internal and external stakeholders.
- Defined and monitored security KPIs, ensuring targets were met.
- Managed budgeting processes, achieving a 15% reduction in operational expenditure.
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.
Discover over 15,000 top freelancers
Statistics of experts using Machine Learning
Aggregated from the professional profiles of matched freelancers.
Experience
17 years
Position duration
3.2 years
Positions per freelancer
8
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Manufacturing, Banking and Finance
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
90%
Master's degree or higher
76%
Doctorate
33%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
96%
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 Austria 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 Austria 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 covers
Machine Learning turns data into predictions, rankings, and decisions. It is used for forecasting demand, spotting anomalies, classifying text or images, and personalizing products. Strong professionals connect the model to a real business goal, not just the training data.
Common tools
- Python for data work and model training
- scikit-learn for classic ML pipelines
- TensorFlow and PyTorch for deep learning
- XGBoost and similar libraries for structured data
- SQL, notebooks, and cloud services for data access and delivery
Where it fits
Companies bring in freelance specialists when a product needs better recommendations, fraud detection, churn prediction, search relevance, or automation around manual review. In Austria, this often means working with teams in manufacturing, finance, logistics, and software, either on-site or remotely.
Strong skills
A good Machine Learning professional understands data quality, feature engineering, evaluation, and deployment. They can explain trade-offs between accuracy, latency, interpretability, and maintenance. They also know when a simple baseline is better than a complex model.
Delivery signs
- Clear problem framing and success criteria
- Reproducible experiments and clean code
- Honest evaluation on real-world data
- Deployment thinking for APIs or batch jobs
- Documentation that helps teams maintain the model
When to hire
Bring in outside help when your team has data but lacks model design, when an old model no longer performs well, or when you need fast support for a proof of concept. Freelancers are also useful for short, focused work such as model review, tuning, or transfer to production.
Frequently asked questions
What clients ask us most about Machine Learning — answered in short.
Machine Learning is used to make data-driven predictions and automate decisions. Companies use it for forecasting, recommendation systems, fraud checks, text classification, image recognition, and anomaly detection. It is most useful when rules alone are too rigid or too slow to maintain.
Machine Learning goes beyond reporting what happened and can learn patterns that help predict what may happen next. Traditional analytics is still important for dashboards, KPIs, and clear business summaries. In many projects, the best setup combines both.
A strong Machine Learning specialist usually knows Python, SQL, data preparation, model evaluation, and deployment basics. Helpful extras include statistics, cloud tooling, and experience with scikit-learn, TensorFlow, or PyTorch. They should also be able to talk clearly with product and data teams.
A Machine Learning freelancer should understand the business goal, available data, target users, and how the model will be used. Clear input on labels, edge cases, and constraints saves time later. If the problem is vague, the first step should be framing rather than model training.
A Machine Learning proof of concept is enough when you need to test whether data can solve the problem at all. Deeper support is needed when the model must run in production, stay stable over time, or integrate with existing systems. Production work also needs monitoring, retraining plans, and careful evaluation.
Yes, Machine Learning work is often well suited to remote collaboration, especially for data review, experimentation, and model tuning. On-site time can help when sensitive data, legacy systems, or close stakeholder workshops are involved. Many Austrian teams use a mix of both.
Look for someone who can explain data choices, model limits, and evaluation results in plain language. A strong Machine Learning professional shows working code, reproducible experiments, and a clear path from prototype to production. Be cautious if the focus stays on algorithms but ignores data quality and business impact.
Machine Learning and ML mean the same thing. AI is the broader field, while machine learning is a practical way to build systems that learn from data. When hiring, the useful question is not the label but whether the specialist has solved the kind of problem you face.
The average hourly rate of freelancers in Austria who have used Machine Learning in their recent projects is 105 €, which corresponds to a daily rate of about 840 € based on an 8-hour working day.
Of the freelancers in Austria who have used Machine Learning in their recent projects, 90% hold at least a Bachelor's degree, 76% hold at least a Master's degree, and 33% hold a doctorate.
On average, freelancers in Austria who have used Machine Learning in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 3.2 years.
The most common languages among freelancers in Austria who have used Machine Learning in their recent projects are German (96%), English (96%), and French (25%).
The most common industries among freelancers in Austria who have used Machine Learning in their recent projects are Information Technology (83%), Manufacturing (50%), and Banking and Finance (46%).
The most common business areas among freelancers in Austria who have used Machine Learning in their recent projects are Information Technology (96%), Product Development (71%), and Project Management (71%).
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.
Vienna Graz 
Vienna Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
