Artificial Neural Network Experts in Austria
matched in minutes from over 15,000 CVsHire experts who design, train and optimize neural models for computer vision, language processing and predictive systems. FRATCH connects you quickly with vetted, available freelancers whose skills match your technical and business requirements.
Meet FRATCH Experts in Austria, who have recently used Artificial Neural Network
Alexander P.
Last position:
Owner & Lecturer at Artellico / Own Company for AI Governance and Data Products
- Consulting and interim management at the intersection of IT operations and regulation
- Impact analysis and implementation planning for NISG 2026 and EU AI Act, including risk management and reporting and evidence processes
- Training for governing bodies and employees on regulatory obligations
- Teaching assignments in Data & Information Management and Human-Machine Interaction at Hochschule Burgenland, since 2023
- Supervision of master’s theses and participation in the examination board
- Expert presentations in 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
- Connection to bank account systems via SEPA direct debit mandates and message formats according to ISO 20022 (pain.008, camt.053)
- MLOps and AIOps in ongoing operations
- Own applications under own brand: shared code base, 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 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
Matthias K.
Last position:
Business Architect at E5GTEC
- Analysis of extended requirements related to existing controllers in an industrial plant
- Creating concepts for storing and visualizing sensor data
- Communication with PLCs
- Microservice architecture
- Unified architecture
- AI-based evaluations of sensor data
- Technologies used: .NET 8, Minimal API, Postgres, MQTT, RabbitMQ
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.
Maximilian A.
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.
Alexander K.
Last position:
Freelancer at Zirkonzahn
- Implemented features into existing software, including applications for neural networks and rendering features using C# and WPF
- Collaborated in a team of 3 people
Philipp H.
Last position:
Self-employed R&D focusing on medical imaging (freelancer) at GoCompute
- Image visualization
- Image quality improvements
- Image reconstruction
- Artefact reduction
- Algorithm development, enhancement, and porting (GPU)
- C++
- CUDA
- OpenGL
- OpenCL
- VTK
- ITK
- DICOM
- Realized projects for CADS GmbH and medPhoton, a Brainlab company
Discover over 15,000 top freelancers
Statistics of experts using Artificial Neural Network
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
3.2 years
Positions per freelancer
8
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Healthcare, Education
Certification focus areas
Project Management, Information Technology, Logistics
Bachelor's degree or higher
100%
Master's degree or higher
100%
Doctorate
50%
Certifications per freelancer
2
Most common languages
German, English, Spanish
Speak two or more languages
100%
Based on our profile pool as of 16 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Austria are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Austria using Artificial Neural Network
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 16 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Artificial Neural Network 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 (83%)
- Healthcare (67%)
- Education (50%)
- Manufacturing (50%)
- Professional Services (50%)
- Government and Administration (50%)
- Aerospace and Defense (33%)
- Banking and Finance (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What neural networks do
An Artificial Neural Network is a machine learning model inspired by connected biological neurons. It learns patterns from training data and applies them to tasks such as image recognition, language analysis, forecasting, recommendation and anomaly detection. The model can improve as it receives relevant, well-prepared data.
Common applications
Companies use neural networks when rules are too complex to write manually or when large datasets contain useful hidden patterns.
- Classify images, documents, audio and sensor signals
- Detect objects, defects, fraud and unusual behaviour
- Forecast demand, equipment states and customer actions
- Generate or summarize text and extract structured information
- Personalize recommendations and search results
Frameworks and tooling
Strong specialists work across Python-based machine learning workflows and understand the trade-offs between model quality, speed and operational cost. Common tools include PyTorch, TensorFlow, Keras, scikit-learn, Jupyter and experiment tracking systems. They also connect models with data warehouses, APIs, cloud services and production monitoring.
When to bring in specialists
Freelance expertise helps when a company has promising data but lacks a reliable path from experiment to production. It is also useful for improving an existing model, reducing inference latency, building a proof of concept or reviewing a machine learning architecture. Austrian teams may work remotely with international professionals or combine remote delivery with on-site workshops when domain knowledge and local collaboration matter.
Skills beyond the model
A capable professional understands data preparation, feature engineering, labeling strategy, validation and model evaluation. They can choose between a dense network, convolutional model, recurrent approach, transformer or a simpler baseline instead of forcing every problem into a neural solution. Experience with Docker, cloud deployment, version control, APIs and responsible data handling supports dependable delivery.
Signs of quality
Look for evidence that a specialist has measured real-world performance rather than only training accuracy. A strong project discussion should cover data leakage, class imbalance, explainability, drift and failure cases.
- Clear evaluation criteria linked to business outcomes
- Reproducible experiments and documented assumptions
- Careful separation of training, validation and test data
- Monitoring plans for changing data and model behaviour
- Practical communication with product and domain teams
Frequently asked questions
Curious about Artificial Neural Network? Here are the answers that come up again and again.
An Artificial Neural Network learns relationships in data and uses them to make predictions or classifications. Companies apply neural networks to computer vision, speech, text processing, forecasting, recommendations, quality inspection and anomaly detection.
An Artificial Neural Network can learn complex representations directly from large or unstructured datasets, while many traditional models rely more heavily on hand-crafted features. Neural networks are not automatically better; tree-based models, linear models or rule-based systems may be clearer, faster or more effective for structured business data.
A strong neural network specialist should understand Python, data pipelines, statistics, model evaluation and software version control. Useful adjacent skills include PyTorch or TensorFlow, cloud and container deployment, SQL, APIs, experiment tracking and responsible handling of sensitive data.
The right level of experience depends on the risk, data quality and production requirements of the project. A proof of concept may need a specialist who can test assumptions quickly, while a customer-facing or safety-sensitive system requires demonstrated experience with validation, monitoring, deployment and failure analysis.
Yes. Artificial Neural Network work is often suitable for remote collaboration because data reviews, experiments, code and model evaluations can be shared through secure tools. On-site sessions can still help with domain workshops, data access decisions and alignment with Austrian product or operations teams.
An Artificial Neural Network specialist should select the model according to the data and task rather than fashion. Convolutional models are often effective for spatial signals such as images, while transformers are suited to many sequence and language tasks; a simpler baseline should be tested as a reference.
Ask how the professional defines success, prevents data leakage and handles imbalanced or changing data. A reliable Artificial Neural Network professional explains trade-offs clearly, compares against meaningful baselines and provides reproducible evaluation instead of presenting training accuracy alone.
Before starting, an Artificial Neural Network freelancer should clarify the business objective, available data, labeling process, access restrictions, evaluation criteria and expected production environment. They should also agree on ownership of experiments, documentation, deployment responsibilities and how model performance will be monitored after release.
The average hourly rate of freelancers in Austria who have used Artificial Neural Network in their recent projects is 104 €, which corresponds to a daily rate of about 834 € based on an 8-hour working day.
Of the freelancers in Austria who have used Artificial Neural Network in their recent projects, 100% hold at least a Bachelor's degree, 100% hold at least a Master's degree, and 50% hold a doctorate.
On average, freelancers in Austria who have used Artificial Neural Network in their recent projects have 18 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 Artificial Neural Network in their recent projects are German (100%), English (100%), and Spanish (17%).
The most common industries among freelancers in Austria who have used Artificial Neural Network in their recent projects are Information Technology (83%), Healthcare (67%), and Education (50%).
The most common business areas among freelancers in Austria who have used Artificial Neural Network in their recent projects are Information Technology (100%), Product Development (83%), and Project Management (67%).
Main locations of FRATCH Experts, who have recently used Artificial Neural Network
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:
- Germany
- Austria
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