Find the perfect AI Engineers in Austria in minutes from 15,000 CVs with the power of AI
Need help with LLM apps, machine learning pipelines, MLOps, or model evaluation? Work with AI engineers who can build production-ready systems, connect data sources, and ship reliable automation. Get fast, precise matching with vetted, available freelancers.
About the role
What they build
AI engineers turn business problems into working systems. They design and ship models, prompts, retrieval pipelines, and automation that can run in production. Typical deliverables include:
- LLM-powered assistants and internal copilots
- Data pipelines for training and inference
- Model evaluation setups and test cases
- MLOps workflows for deployment and monitoring
Core skills
A strong AI engineer combines software engineering with practical machine learning. They should be comfortable with Python, APIs, vector databases, cloud services, and model integration. They also need to understand data quality, latency, cost, and safety, because a good prototype is not enough.
Tools and stack
The stack depends on the use case, but common tools include Python, SQL, PyTorch, TensorFlow, scikit-learn, LangChain, OpenAI or open-weight models, Docker, Kubernetes, and cloud platforms such as AWS, Azure, or Google Cloud. For production work, logging, monitoring, and version control matter just as much as model choice.
When companies bring them in
Companies hire freelance AI engineers when they need a project to move now, not after a long hiring process. That is common for proof of concepts, internal automation, search and knowledge systems, document processing, or the move from an experiment to a stable product. In Austria, they are often brought into manufacturing, software, finance, and industrial companies that want to connect AI work to existing systems and data teams.
What good looks like
The best AI engineer is clear about trade-offs. They do not just tune models; they choose the right architecture, define success criteria, and explain what can fail.
- Builds maintainable code, not only demos
- Understands data access, privacy, and system limits
- Works well with product, backend, and data teams
- Writes clean tests, prompts, and evaluation logic
- Can adapt from ML engineering to GenAI implementation
Collaboration setup
Many projects start remotely and only need on-site time for workshops, stakeholder alignment, or work with sensitive internal systems. Freelancers should be able to communicate clearly in English, and sometimes German, depending on the team. The best outcomes come when scope, data access, and ownership are defined early, especially for AI engineer, machine learning engineer, or ML engineer assignments.
Meet FRATCH AI Engineers
Manuel Pasieka
AI Engineer
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.
Daniel Schlager
Full-Stack Developer & AI Engineer
Last position:
AI Automation in E-Commerce at Looops
- AI automation roadmap for a D2C/B2B e-commerce company.
- Customer service bot with RAG over support tickets and product data, OCR pipeline for incoming invoices with writeback to Business Central, lead gen and posting automation.
- Deterministic n8n workflows with EU-hosted models.
- n8n, RAG / Mistral, Qwen/BGE embeddings / Business Central API, HubSpot, Shopify / Scaleway, S3 / Claude Code, OpenCode.
Marcel Steger
Senior AI Engineer
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.
Alexander Lechner
Guest lecturer in Artificial Intelligence (Master’s Level)
Last position:
Guest lecturer in Artificial Intelligence (Master’s Level) at FH des BFI Wien
- Teaching & presenting
- Communication
- Effectively communicate complex technical topics to non-technical audiences through lectures
- Guided non-technical students from zero knowledge to confidently understanding and applying algorithms to achieve business outcomes
Mario Tuta
Freelance Data Scientist & AI Engineer
Last position:
External Lecturer at FH Kufstein Tirol – University of Applied Sciences
- Study: Data Science & Intelligent Analytics
- Module: Big Data Processing
Herbert Ritsch
Lateral Entry Teacher
Last position:
Lateral Entry Teacher at BRG Hermagor and HLW Hermagor; Caritas School for Social Professions; Vienna University of Economics and Business
Subjects taught: Business Administration & Economics, Computer Science, Geography & Postgraduate Business Education for the 2024/25 school year at BRG Hermagor and HLW Hermagor (Economics & Informatics), 22 teaching hours
Teaching for the 2026 school year at Caritas School for Social Professions in Wiener Neustadt, Computer Science; 8 teaching hours; current position at Vienna University of Economics and Business
Financial literacy classes for 1st and 2nd grades at HLW and for the 1-year Commercial School with a financial license, including the Money Matters program and simulated job interviews incorporating financial knowledge
Sustainability reporting for 5th-grade HLW and financial market education in cooperation with the Vienna Stock Exchange
Junior companies with 2nd and 3rd year HLW students, including participation at the Vienna Trade Fair in February 2025 and the Klagenfurt Regional Competition in April 2025
AI workshop for upper secondary students at BRG and HLW Hermagor
Supervision of diploma theses/VWA with a focus on AI
Discover over 15,000 top freelancers
AI Engineers statistics
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
2.2 years
Positions per freelancer
19
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Education, Information Technology, Manufacturing
Certification focus areas
Information Technology, Research and Development, Product Development
Bachelor's degree or higher
100%
Master's degree or higher
100%
Doctorate
25%
Certifications per freelancer
2
Most common languages
German, English, Spanish
Speak two or more languages
100%
Daily Rate Distribution
The chart shows how the daily rates of freelancers in this role 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. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Average rates for AI Engineers & Seniority distribution
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.
Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Frequently Asked Questions
Looking for clear information? Everything important about FRATCH is here
A AI engineer builds the systems that make AI usable in real work. That can mean model integration, retrieval-augmented search, automation, evaluation, deployment, or monitoring. The job is not just training models; it is turning them into software a team can trust.
Look for strong Python skills, solid software engineering habits, and hands-on experience with machine learning or LLM-based systems. They should understand APIs, data pipelines, testing, cloud deployment, and basic MLOps. A good freelancer can also explain trade-offs in plain language.
The titles overlap, but the focus can differ. A machine learning engineer often centers on training, optimization, and deployment of predictive models, while an AI engineer may work more broadly across LLM applications, automation, retrieval systems, and production integration. In practice, many companies use the terms interchangeably.
A freelancer is a strong choice when you need a specific AI project delivered quickly or when the scope is still changing. It also helps when you need specialist support for a prototype, a hard integration, or a short product push. If you do not yet know the final architecture, a freelance AI engineer can help shape it before you hire long term.
Most AI engineering work can be done remotely if the team can provide data access, clear requirements, and fast feedback. On-site time is useful for early workshops, alignment with product and engineering teams, or work that touches sensitive systems. In Austria, many clients use a hybrid setup for that reason.
Typical deliverables include a working prototype, source code, evaluation scripts, integration layers, and deployment instructions. For production work, you should also expect monitoring, logging, and documentation. If the project uses LLMs, prompt design and safety checks are often part of the handover.
A strong AI engineer produces something that works under real conditions, not just in a demo. Look for clean code, clear evaluation logic, good documentation, and a realistic view of risks and limits. They should be able to explain why they chose a model, tool, or architecture.
Companies and freelancers may also use titles such as machine learning engineer, ML engineer, or AI developer. The exact title matters less than the actual work: building, integrating, and operating intelligent systems in production. Ask for examples that match your use case, not just the label on the profile.
The average hourly rate for AI Engineers in Austria is 104 €, which corresponds to a daily rate of about 830 € based on an 8-hour working day.
Of the freelancers working as AI Engineers in Austria, 100% hold at least a Bachelor's degree, 100% hold at least a Master's degree, and 25% hold a doctorate.
On average, freelancers working as AI Engineers in Austria have 18 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers working as AI Engineers in Austria are German (100%), English (100%), and Spanish (17%).
The most common industries among freelancers working as AI Engineers in Austria are Education (83%), Information Technology (83%), and Manufacturing (83%).
The most common business areas among freelancers working as AI Engineers in Austria are Business Intelligence (100%), Information Technology (100%), and Product Development (100%).
FRATCH AI Engineers main locations
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 Countries:
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Philipp Thomaschewski
FRATCH CEO
