Llama Experts in Nuremberg
matched in minutesHire experts who fine-tune Meta Llama models, build retrieval-augmented applications and connect generative AI to business systems. FRATCH matches you precisely with vetted, available freelancers who fit your project and can start quickly.
Meet FRATCH Experts in Nuremberg, who have recently used Llama
David O.
Last position:
Machine Learning Researcher at Pattern Recognition Lab, FAU
- Fine-tuned and evaluated alternative backbone architectures for the AFFGAN handwriting style encoder to better capture writer-specific features, benchmarking against the original baseline architecture and replacing the legacy VGG19 architecture with a custom Transformer-based encoder.
- Extended the system beyond word-level synthesis to line-level handwriting generation, integrating and adapting an existing line-generation architecture to support full-sentence output.
- Deployed the handwriting generation pipeline as a web application, enabling users to select a writing style, input custom text, and instantly generate a corresponding handwriting image.
- Integrated TrOCR into a teacher–student distillation framework to evaluate and improve readability of generated handwriting, improving OCR accuracy by 20% over the baseline.
- 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.
Tech: PyTorch, Python, GANs, CNN, ViT, TrOCR, Streamlit, CUDA.
Muntaha S.
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.
Kashyap K.
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.
Puranjan B.
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.
Uddipan B.
Last position:
Research Team Member at Munich Music Labs, TUM
- Focused on exploring the intersection of Music and AI.
Ekaansh K.
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
Discover over 15,000 top freelancers
Statistics of experts using Llama
Aggregated from the professional profiles of matched freelancers.
Experience
7 years (Germany: 14 years)
Position duration
1.5 years (Germany: 1.8 years)
Positions per freelancer
5 (Germany: 11)
Top business areas
Product Development, Research and Development, Information Technology
Top industries
Information Technology, Manufacturing, Education
Certification focus areas
Business Intelligence, Information Technology, Research and Development
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
100% (Germany: 82%)
Certifications per freelancer
2
Most common languages
English, German, Bangla
Speak two or more languages
100% (Germany: 98%)
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Nuremberg 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 Nuremberg using Llama
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Llama 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%)
- Manufacturing (83%)
- Education (67%)
- Automotive (50%)
- Arts and Crafts (17%)
- Chemical (17%)
- Healthcare (17%)
- Professional Services (17%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Llama does
Llama is Meta’s family of open-weight large language models for text generation, summarisation, extraction, classification and conversational applications. Teams use Llama to create private AI assistants, search interfaces and workflow automation while keeping control over model hosting, data access and application behaviour.
Models and ecosystem
The Llama ecosystem covers model variants, instruction-tuned releases and deployment options for cloud, edge and self-managed infrastructure. Strong specialists work with Hugging Face, PyTorch, Transformers, vLLM, Ollama and quantisation tools. They select a suitable model, prepare prompts and connect inference to reliable application services.
Common deliverables
- Retrieval-augmented generation with company documents
- Internal knowledge assistants and support interfaces
- Document classification, extraction and summarisation
- Fine-tuning or adapter training for domain language
- Production inference APIs with monitoring and safeguards
When companies need expertise
Freelance expertise is useful when a proof of concept must become a dependable product, or when an existing AI service needs more control over data and deployment. Companies in Nuremberg can involve specialists for on-site workshops, remote delivery or a mixed setup. German-language communication may matter when the model serves local customers, employees or regulated processes.
Skills beyond the model
A capable Llama professional understands more than prompt writing. Relevant skills include Python, PyTorch, data preparation, vector databases, embeddings, API design, containerisation and cloud or GPU operations. They also define evaluation sets, access controls, human review paths and fallback behaviour so that generated output remains useful and traceable.
Choosing a strong specialist
Look for evidence of complete Llama projects rather than isolated experiments. A strong professional can explain model selection, context limits, retrieval quality, latency, cost control and failure handling in clear terms. Ask how they test factual accuracy, protect sensitive information and measure whether the system helps its intended users before production rollout.
Frequently asked questions
Before you brief your next project: the most common questions about Llama.
Llama is used for assistants, document processing, semantic search, content drafting, classification and structured data extraction. It can support customer service, internal knowledge work, research and workflow automation when paired with suitable retrieval, validation and access controls.
Llama gives teams more control over model hosting, data handling, fine-tuning and infrastructure choices. Hosted alternatives can reduce operational work and offer strong general performance, while Llama may suit companies that need self-managed deployment, customisation or tighter control of sensitive information.
A strong Llama freelancer often combines model work with Python, PyTorch, Hugging Face Transformers, vector search, embeddings and API integration. Experience with Docker, GPU serving, cloud infrastructure, evaluation design and prompt security is also valuable for production systems.
Llama projects do not always require training a model from scratch. Many applications rely on retrieval-augmented generation, careful prompting, adapters or targeted fine-tuning, so the right level of experience depends on data quality, domain complexity, privacy needs and the required production reliability.
Llama can be deployed in an environment controlled by the company, which may help keep confidential data within defined systems. Security still depends on the complete design, including document permissions, logging, retention, model access, prompt handling and protection against data leakage.
Llama work is often well suited to remote collaboration because code, models, datasets and evaluation results can be shared digitally. On-site sessions in Nuremberg can still help with discovery, data access, stakeholder alignment and training, especially when German-language communication is important.
Ask a Llama specialist to explain a complete delivery path from data preparation and model choice to evaluation, deployment and monitoring. Request a clear account of how they handle hallucinations, prompt injection, access rights, latency and changes in output quality.
Llama is commonly used with Meta’s model releases, Hugging Face, PyTorch, vLLM, Ollama and quantisation workflows. Professionals should understand the trade-offs between local inference, managed hosting and GPU serving, as well as the licensing terms and operational requirements of the chosen model release.
The average hourly rate of freelancers in Nuremberg, Germany who have used Llama in their recent projects is 36 €, which corresponds to a daily rate of about 285 € based on an 8-hour working day.
Of the freelancers in Nuremberg, Germany who have used Llama in their recent projects, 100% hold at least a Bachelor's degree and 100% hold at least a Master's degree.
On average, freelancers in Nuremberg, Germany who have used Llama in their recent projects have 7 years of professional experience, with a single engagement typically lasting around 1.5 years.
The most common languages among freelancers in Nuremberg, Germany who have used Llama in their recent projects are English (100%), German (83%), and Bangla (33%).
The most common industries among freelancers in Nuremberg, Germany who have used Llama in their recent projects are Information Technology (83%), Manufacturing (83%), and Education (67%).
The most common business areas among freelancers in Nuremberg, Germany who have used Llama in their recent projects are Product Development (100%), Research and Development (100%), and Information Technology (83%).
Main locations of FRATCH Experts, who have recently used Llama
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.
Berlin 
Munich Request a free demo
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Philipp Thomaschewski
FRATCH CEO
