Hello, I'm Christoph

I am a freelance AI engineer with a strong background in machine learning, MLOps and distributed systems. I have over 5 years of experience building AI systems and more than a decade designing distributed systems.

I work through every phase of the AI lifecycle—from early prototypes to large-scale production systems. I combine the latest AI research with practical engineering, working closely with my clients to ensure our projects go well beyond research demos and deliver value in production.

Outside of client projects, I’m also engaged in open-source work and exploratory research, currently focusing on cognitive architectures and agent-based systems.

I’ve helped companies like MerlinOne and Canto build and deploy large-scale AI search platforms that process and index millions of images and videos in real time, combining distributed inference (PyTorch, Triton, Kubernetes) with distributed vector databases (Milvus) for scalable, low-latency retrieval. These platforms are used by thousands of customers including The Associated Press - enabling them to use advanced visual image and video search simply by describing visual content. I also scaled computer vision models on AWS to process over 100M+ assets and conducted model fine-tuning to optimize performance on domain-specific data.

At cyan Security Group, I designed a comprehensive MLOps platform (Databricks, MLFlow, AWS) that automated data pipelines, model deployment, and real-time monitoring —allowing rapid iteration from prototype to production. I also trained and integrated computer vision models into the cyan security suite, including child protection and content filtering products, to detect malicious or sensitive web content.

As a distributed systems engineer, I have developed a reactive microservices framework and built a distributed messaging infrastructure to enable high-throughput, event-driven communication—ensuring scalability and fault tolerance across mission-critical client services.

Skills & Expertise

Curious if I can help with your project? Whether you're starting with a proof-of-concept or scaling an AI solution to production, I am here to support you.

• AI Engineering - Implementation of AI systems from RAG solutions to LLM-based agentic systems.
• Machine Learning – End-to-end model development, training, fine-tuning, and deployment.
• MLOps & Platform Engineering – Building robust pipelines that streamline data management, model development, deployment and monitoring.
• Distributed Systems & Architecture – Designing reliable, fault-tolerant infrastructures that efficiently scale with workload demands.

Technologies

Below are some of the technologies and tools I use in my day-to-day work:

🤖 AI & Machine Learning

PyTorch, Hugging Face (Transformers, Datasets, Accelerate, TGI), Scikit-learn, LangChain, Haystack, llama.cpp, Triton, Faiss, Milvus, Weaviate, Qdrant

🧠 Model APIs

Anthropic, OpenAI, Gemini

🛠️ Application Development & Data Engineering

FastAPI, Flask, Apache Kafka, Apache Spark, Delta Lake, Databricks

🌐 Infrastructure

Docker, Kubernetes, AWS, Azure, Google Cloud Platform, Terraform, GitHub Actions