Machine Learning Experts in Vienna
for smarter products, matched in minutes with vetted and available freelancersHire experts who build predictive models, recommendation systems and computer vision solutions with Python, scikit-learn, PyTorch and TensorFlow. FRATCH matches you quickly and precisely with vetted, available freelancers for your Machine Learning project.
Meet FRATCH Experts in Vienna, who have recently used Machine Learning
Alexander P.
Last position:
Owner & Lecturer at Own company for AI governance and data products, Vienna
- Consulting and interim management at the interface between IT operations and regulation
- Impact analysis and implementation planning for NISG 2026 and the EU AI Act, including risk management and reporting and evidence processes
- Training for governing bodies and employees on regulatory obligations
- Lectures in Data & Information Management and Human-Machine Interaction at University of Applied Sciences Burgenland, since 2023
- Supervision of master’s theses and participation in the examination board
- Presentations for business and educational institutions
- Design and development of data and AI products, platforms and pipelines
- Privacy-first architectures and zero-knowledge encryption, cloud-native on EU infrastructure
- MLOps and AIOps in live operations
- Own applications under own brand: shared codebase, separate delivery for each target device
- AI-assisted software development (vibe coding), complete agentic pipelines, code generation, implementation, automated testing, CI/CD and release cycles
- Publications on the EU AI Act, NIS2, DORA, CRA and CER as an integrated governance system
- Publications on data sovereignty, cloud economics and industrial image processing
- AI governance / compliance: data quality, Responsible AI, EU AI Act readiness, risk classification, AI ethics
Manuel P.
Last position:
AI Engineer at Misumi Europe GmbH & Motius GmbH
- Designed and built a next-generation NLP platform to accelerate sales-driven customer service through intelligent request analysis and routing, reducing average customer query response time by 30%.
- Architected a hybrid NLP system combining Large Language Models (LLMs) with traditional NLP pipelines for robust, explainable results.
- Developed request classification and routing mechanisms to accelerate customer support teams in handling customer queries faster and more accurately.
- Optimized LLM based data extraction and classification with context engineering.
- Integrated the platform into customer service processes, reducing response times and enhancing workforce efficiency.
Stefan D.
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 S.
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.
Marc-Anthony T.
Last position:
Software Developer at Dawnguard.AI
- Foundational member of the backend TypeScript team, responsible for translating the initial product concept into a fully functional platform.
- Architected the core resource discovery engine for Azure and AWS, successfully enabling the frontend to visualize complex cloud environments and empowering the AI to evaluate architectural patterns.
- Engineered and scaled distributed APIs and dynamic CosmosDB schemas, ensuring the database and backend architecture could seamlessly adapt to rapidly evolving product requirements.
- Accelerated cross-functional testing by developing custom data-generation tools, allowing the AI and frontend teams to simulate and test against large-scale, artificial cloud architectures.
- Drove end-to-end feature delivery by partnering closely with AI, frontend, and business stakeholders to align technical implementation with the strategic vision of the Dawnguard platform.
Fabio G.
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 B.
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 G.
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 G.
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 N.
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.
Atif Y.
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)
Kevin L.
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.
Robert P.
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
16 years
Position duration
2.7 years
Positions per freelancer
9
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Media and Entertainment
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
90%
Master's degree or higher
90%
Doctorate
20%
Certifications per freelancer
2
Most common languages
German, English, French
Speak two or more languages
92%
Based on our profile pool as of 19 Sep 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Machine Learning experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (69%)
- Banking and Finance (54%)
- Media and Entertainment (46%)
- Education (38%)
- Manufacturing (38%)
- Transportation (31%)
- Automotive (23%)
- Energy (23%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Machine Learning does
Machine Learning, often shortened to ML, enables software to learn patterns from data and produce predictions, classifications or recommendations. It supports fraud detection, demand forecasting, search, personalization, document processing and intelligent automation. The right approach depends on the data, decision process and business outcome.
Models and project work
Professionals turn a business question into a measurable modelling task. They prepare datasets, select features, train models and validate results against realistic conditions. Typical deliverables include:
- Predictive models for demand, risk or customer behavior
- Recommendation and ranking systems
- Text classification, extraction and language workflows
- Image, video and sensor-data analysis
Ecosystem and tooling
Most ML work uses Python alongside pandas, NumPy and scikit-learn. Deep learning projects commonly rely on PyTorch or TensorFlow, while notebooks support exploration and experiment tracking tools help compare runs. Strong specialists also understand APIs, databases, containers, cloud services and MLOps practices for reliable deployment.
When companies need expertise
Companies often bring in freelance expertise when internal teams have valuable data but lack modelling capacity, or when a prototype must become a dependable service. Vienna-based organisations in finance, manufacturing, mobility, retail and public services may need support across discovery, model development and production rollout. Remote collaboration works well when data access, documentation and communication are organised clearly.
Production and responsible use
A model is only useful when it performs consistently after release. Experienced professionals create reproducible pipelines, monitor drift, test data quality and define retraining processes. They also address explainability, privacy, bias and access controls, especially when predictions affect customers, employees or regulated decisions.
What strong professionals bring
Look for specialists who connect modelling choices to commercial and operational goals. They can explain assumptions in plain language, challenge weak data and compare a complex model with a simpler baseline. Useful evidence includes clear evaluation methods, documented experiments and successful handover to the teams responsible for software, data and operations.
Frequently asked questions
Not sure where to start with Machine Learning? These answers cover the essentials.
Machine Learning is used to identify patterns in data and support decisions or automated actions. Common applications include forecasting, fraud detection, recommendations, image recognition, text processing and predictive maintenance.
Machine Learning learns behavior from examples rather than relying only on rules written by a professional. It is useful when patterns are difficult to specify manually, but it requires suitable data, careful evaluation and ongoing monitoring.
A strong Machine Learning professional compares all three options against the data, risk and maintenance needs. Rules may be clearer for stable processes, while deep learning is better suited to complex image, audio or language tasks with enough relevant data.
A capable Machine Learning specialist usually works comfortably with Python, SQL, statistics and data preparation. Experience with APIs, cloud infrastructure, containers, MLOps, data privacy and software testing is valuable when a model must run in production.
The right Machine Learning experience depends on the scope and risk of the project. A focused prototype may need modelling and data skills, while a customer-facing system also requires deployment, monitoring, documentation and collaboration with product and software teams.
Yes, Machine Learning projects can often be delivered remotely when secure data access, environments and documentation are available. On-site sessions in Vienna can help with discovery, stakeholder alignment or restricted data, while English is common and German may matter for local communication.
Ask a Machine Learning professional to explain the baseline, validation design, error analysis and limits of a proposed model. Quality also includes reproducible experiments, robust data handling, understandable reporting and a clear plan for monitoring performance after release.
Before beginning Machine Learning work, clarify the business decision, target outcome, available data, access restrictions and success criteria. Also confirm who owns deployment, how predictions will be reviewed and whether the project requires support for regulated or sensitive use cases.
The average hourly rate of freelancers in Vienna, Austria who have used Machine Learning in their recent projects is 103 €, which corresponds to a daily rate of about 823 € based on an 8-hour working day.
Of the freelancers in Vienna, Austria who have used Machine Learning in their recent projects, 90% hold at least a Bachelor's degree, 90% hold at least a Master's degree, and 20% hold a doctorate.
On average, freelancers in Vienna, Austria who have used Machine Learning in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.7 years.
The most common languages among freelancers in Vienna, Austria who have used Machine Learning in their recent projects are German (92%), English (92%), and French (31%).
The most common industries among freelancers in Vienna, Austria who have used Machine Learning in their recent projects are Information Technology (69%), Banking and Finance (54%), and Media and Entertainment (46%).
The most common business areas among freelancers in Vienna, Austria who have used Machine Learning in their recent projects are Information Technology (92%), Business Intelligence (69%), and Product Development (69%).
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
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
