AI Engineers in Nuremberg

• 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.

• Independently managed the POS tender process for food service operations in department stores.

• Structured requirements gathering, both functional and technical.

• Created a management-ready specification as a basis for decision-making by management and IT.

• Market overview of relevant POS providers.

• Close coordination with Galeria's IT and business departments.

• 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.

• 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.