Generative AI Experts in Nuremberg
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Meet FRATCH Experts in Nuremberg, who have recently used Generative AI
Oleg Orlov
Last position:
Senior Software Developer / BI Integration Developer Power BI, C# at Telecommunications
Embedded Analytics & AI-assisted BI
Design and development of an integrated analytics solution based on ASP.NET Core, Power BI Embedded, and LLM services to provide contextual business information.
Development of an AI agent with Function/Tool Calling for secure orchestration of REST APIs, SQL data sources, and technical services within defined business processes.
Build-up of automated BI workflows including workspace management, deployment processes, and scheduled refresh via the Power BI REST API.
Implementation of secure service-to-service communication with Microsoft Entra ID and service principal, as well as integration into existing enterprise system landscapes.
Technologies: ASP.NET Core, C#/.NET, Power BI Embedded, Power BI REST API, LLM API, AI Agents, Function/Tool Calling, Entra ID
David Onaiyekan
Last position:
Research Intern at Pattern Recognition Lab
- Spearheaded the integration of a custom Transformer-based encoder into the AFFGANwriting pipeline, replacing the legacy VGG19 architecture to capture richer, high-fidelity writer-style representations.
- Boosted user-study pick-rates by 40%, demonstrating a significant leap in the perceptual quality and realism of the generated handwriting compared to the baseline model.
- Enhanced OCR performance by 20% by implementing a teacher-student framework that leveraged a TrOCR benchmark model for auxiliary training alignment
Partha Nandi
Last position:
AI Software Developer at Fraunhofer IIS
- Built a custom AI chatbot for an e-commerce client using GPT-4 and LangChain with RAG, reducing customer support ticket volume by 45% and improving response accuracy to 92%.
- Designed and deployed an intelligent document processing system using LlamaIndex, Pinecone, and FastAPI for a FinTech startup, enabling semantic search across 100K+ financial documents.
- Developed multi-agent AI workflows using CrewAI and LangGraph for a marketing agency, automating lead research, content generation, and outreach — saving 20+ hours/week of manual work.
- Created AI-powered automation pipelines using n8n, Make, and Zapier integrated with CRMs (GoHighLevel, HubSpot), reducing manual data entry by 80% for a real estate firm.
- Delivered prompt engineering and LLM fine-tuning consulting for multiple clients, optimizing AI model outputs for customer support, content creation, and data extraction use cases.
- Built production-ready REST APIs with Python and FastAPI to serve AI models on AWS and GCP, handling 10K+ daily requests with 99.9% uptime.
Muntaha Shams
Last position:
AI Engineer (Freelance) at Upwork
- Delivered 40+ AI projects and 23 strategic consultations for international clients (US, Europe, Middle East), achieving a 98% job success rate and building long-term partnerships.
- Developed and deployed production-grade AI solutions in computer vision, NLP, deep learning, and generative AI (LLMs, RAG pipelines, Stable Diffusion, OCR, chatbots), enabling automation and improving client efficiency by up to 70%.
- Designed and fine-tuned large language models (LLMs), including prompt engineering and integration with enterprise knowledge bases, leading to smarter decision-making and reduced manual effort.
- Built real-time computer vision applications (detection, segmentation, OCR) and integrated them into business systems, significantly enhancing accuracy and scalability.
- Consulted startups and enterprises on AI strategy, architecture, and deployment (cloud & on-premise), accelerating product development and reducing time-to-market.
- Managed complete AI project lifecycles (requirements gathering, solution design, deployment, support) in agile, international, and cross-functional environments, ensuring high-quality delivery.
Tobias Von Dewitz
Last position:
Managing Partner at Unwritten GmbH
- Pioneer work in personalized AI: development of a framework for “Interactive Content” (RAG) for novels, lectures, expert debriefing
- Successful launch of Einbug, the Pantopia chatbot, with media resonance (SZ interview)
- Creation of compelling AI personalities: AI blog ([link]), 100% personalized learning environments, Perry Rhodan, and others.
Puranjan Bandyopadhyaya
Last position:
Internship - Generative AI at Continental
- Gathered tire images and their feature descriptions.
- Cleaned dataset of image metadata using pandas.
- Stored image feature embeddings in Chroma vector db.
- Used image augmentations to increase dataset size.
- Used sklearn to create shuffled datasets and imbalanced-learn to balance class sizes in dataset.
- Used PyTorch to train and test different neural networks.
- Validated model using custom accuracy metric based on similarity search in ChromaDB.
- Visualized accuracy predictions using matplotlib.
- Plugged trained model into DreamBooth to train stable diffusion model and generate new images of tires.
- Created custom Docker image in Amazon Elastic Container Registry for machine learning script.
Simone Pfliegel
Last position:
Independent Expert and Assessor at EIT Culture & Creativity
- Independent expert and assessor for the European Institute of Innovation and Technology (EIT), Culture & Creativity
- Review and assessment of European innovation and funding applications based on defined quality and selection criteria
- Evaluation of relevance, level of innovation, feasibility, impact, scalability, and sustainability
- Professional focus areas: artificial intelligence, EdTech, digital transformation, education, innovation, and creative industries
- Analysis of complex project concepts, consortia, impact strategies, and European cooperation projects
- Preparation of well-founded, clear evaluation and selection assessments Experience at the intersection of education, technology, innovation, and European funding programs
Ralph Navasardyan
Last position:
AI Lead Engineer Car Configurator for leading German premium manufacturer at e-ntegration GmbH
- Intent-driven approach to configure all models across all series automotive in all distribution markets of this car manufacturer
- Developed a customer-facing, conversation-driven integration layer to achieve 100% hallucination-free technical configurations
- Utilized Microsoft Azure AI Services: AI Foundry, Agent Service, AI Search; Prompt Shield Services; Content Security; Terraform; API Gateway; AI Gateway; Container Services; Azure Agent SDK; Agent Skills; RAG; MCP Servers and tools
Ekaansh Khosla
Last position:
Master thesis - LLM powered RAG System at Friedrich-Alexander-Universität Erlangen-Nürnberg
- Developed a RAG system to automate student queries with 96% accuracy, built using FastAPI and LangChain and deployed on the university server with Docker.
- Evaluated performance using RAGAS, comparing LLMs (Llama3.3, Llama3.1, GPT-4o-mini), vector embeddings, and various retrieval techniques within the RAG pipeline.
- Technical Skills: Python, FastAPI, Docker, AWS, LangChain, LangSmith, NLP, HTML, CSS
Kashyap Khunt
Last position:
Master’s Thesis - Synthetic Data Generation for Quality Inspection at Schaeffler Technologies AG
- Developed a synthetic data generation framework using 3D simulation (NVIDIA Omniverse) and Generative AI (Stable Diffusion) to model and augment industrial surface defects.
- Trained and evaluated Computer Vision models (YOLO, DETR), achieving 94% detection accuracy on real-world samples and demonstrating successful simulation-to-reality transfer.
- Applied domain adaptation to improve simulation-to-reality transfer, enabling scalable Industrial AI for automated quality inspection and reducing manufacturing downtime.
Ralf Thomas
Last position:
Director Global Cloud - Quality & Compliancy at Eviden
- Leading a global team for quality assurance and compliance in cloud services
Discover over 15,000 top freelancers
Statistics of experts using Generative AI
Aggregated from the professional profiles of matched freelancers.
Experience
16 years
Position duration
2.2 years (Germany: 2.3 years)
Positions per freelancer
9
Top business areas
Information Technology, Product Development, Research and Development
Top industries
Information Technology, Manufacturing, Automotive
Certification focus areas
Information Technology, Research and Development, Business Intelligence
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
91% (Germany: 74%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
English, German, Bangla
Speak two or more languages
100% (Germany: 98%)
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 Nuremberg 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 Nuremberg using Generative AI
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
Generative AI is used to create text, images, code, audio, and structured outputs from prompts and data. Companies bring in specialists to build ChatGPT-style assistants, content pipelines, internal knowledge tools, and workflow automation that relies on large language models.
Typical work
- Prompt design and testing
- LLM integration with business systems
- Retrieval-augmented generation with company data
- Output validation and guardrails
- Model selection for product and support use cases
Ecosystem and tools
Strong professionals work across the GenAI stack, from OpenAI, Azure OpenAI, and Anthropic to open models, vector databases, and orchestration tools. They also know how to connect APIs, manage tokens, and tune prompts for reliable results in production.
When companies need help
Freelance expertise is useful when a team has ideas but no clear model strategy, when a prototype needs to become a stable service, or when output quality is inconsistent. In Nuremberg, this often suits firms that want on-site workshops at first and remote delivery after the architecture is set.
What strong specialists do
Good specialists think beyond prompts. They shape context, evaluate responses, reduce hallucinations, and build clear fallback paths when the model cannot answer well. They also work with product, legal, and data teams so the system fits real constraints.
Hiring signals
Look for specialists who can explain trade-offs between closed and open models, show real evaluation methods, and describe how they handle privacy, grounding, and change control. If the answer is only about prompt tricks, the profile is usually too shallow.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Generative AI.
Generative AI is used to draft text, answer questions from company knowledge, summarize documents, and support content or code workflows. Many teams also use it for assistants, search over internal data, and structured extraction from messy inputs.
Generative AI is the broader field. ChatGPT is a product built on large language models, while GenAI also includes image, audio, and multimodal systems as well as open and closed model stacks.
A strong Generative AI specialist usually knows prompt design, API integration, data handling, and basic evaluation methods. For production work, it helps if they also understand vector search, retrieval design, and privacy constraints.
Generative AI projects need different depth depending on risk and scope. A small prototype may only need a specialist who can test prompts and connect an API, while a customer-facing system needs someone who can add guardrails, evaluation, and fallback logic.
Generative AI is better for language-heavy tasks, open-ended responses, and content generation. Classic machine learning is often a better fit for classification, prediction, and tightly defined outputs, so many teams combine both.
Yes, GenAI work is often remote-friendly because most delivery happens through code, prompts, and shared review. In Nuremberg, on-site time can still help at the start for discovery, stakeholder alignment, or sensitive data discussions.
A good Generative AI specialist shows how they measure answer quality, detect failure cases, and improve outputs over time. Ask for examples of evaluation sets, prompt iterations, and how they handled hallucinations or unsafe responses.
Freelancers working with Generative AI usually need to adapt fast to changing model behavior, shifting product goals, and data access limits. Clear scope, fast feedback, and a defined review process make the work much smoother.
The average hourly rate of freelancers in Nuremberg, Germany who have used Generative AI in their recent projects is 74 €, which corresponds to a daily rate of about 592 € based on an 8-hour working day.
Of the freelancers in Nuremberg, Germany who have used Generative AI in their recent projects, 100% hold at least a Bachelor's degree and 91% hold at least a Master's degree.
On average, freelancers in Nuremberg, Germany who have used Generative AI in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Nuremberg, Germany who have used Generative AI in their recent projects are English (100%), German (91%), and Bangla (9%).
The most common industries among freelancers in Nuremberg, Germany who have used Generative AI in their recent projects are Information Technology (91%), Manufacturing (55%), and Automotive (36%).
The most common business areas among freelancers in Nuremberg, Germany who have used Generative AI in their recent projects are Information Technology (91%), Product Development (82%), and Research and Development (82%).
Main locations of FRATCH Experts, who have recently used Generative AI
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.
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Munich 
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Frankfurt 
Stuttgart 
Dusseldorf 
Dortmund Request a free demo
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Philipp Thomaschewski
FRATCH CEO
