Timon Höfer-Mathematical AI Consultant | PhD-level ML & Computer Vision | Industrial AI, VLMs, Anomaly Detection & AI Product Leadership

I help companies turn mathematically complex AI ideas into robust, testable, and production-ready solutions. My focus is at the intersection of mathematics, machine learning, computer vision, and industrial applications: from technical feasibility and model/data strategy to experiment design, evaluation, product roadmap, and implementation with engineering teams.

I am especially strong where pure prompting or standard ML approaches are not enough: visual quality control, anomaly detection, vision-language models, 6D pose estimation, model evaluation, optimization, explainable AI, and data-driven decision processes. I bring a mathematical background, research experience in deep learning and computer vision, and practical experience in industrial and automotive-related AI contexts. What I do for clients

I help teams set up AI projects in a technically solid way, make risks visible early, and turn vague AI ideas into workable project plans. This includes choosing the right model classes, building evaluation metrics, designing benchmarks, analyzing model errors, data strategy, technical due diligence, and translating between management, product, and engineering.

Typical project roles

AI / ML Consultant for mathematically demanding use cases Applied Machine Learning Engineer for computer vision and multimodal AI Consultant for vision-language models, model evaluation, and AI evaluation AI Product Owner / Technical Product Lead for enterprise AI initiatives Consultant for industrial anomaly detection, quality assurance, and explainable AI Sparring partner for AI strategy, feasibility, architecture, and roadmap

Project types that fit especially well

I am especially interested in projects where AI should not just be demonstrated, but validated in a reliable way and integrated into real processes. This includes industrial computer vision systems, automotive and mobility applications, AI-supported quality assurance, multimodal systems, LLM/VLM evaluation, technical AI strategy, proof of concepts with a clear production path, and roles where research, product, and engineering need to be brought together.

Positioning

My value lies in combining mathematical depth, modern AI methods, and product-oriented execution. I enjoy working with teams that want to solve demanding technical problems and need someone who understands both the model side and the business and product logic.