29.10.2025 aktualisiert
Premiumkunde
100 % verfügbarPerception AI Specialist, Machine Learning Engineer
Magdeburg, Deutschland
Weltweit
PromotionSkills
Maschinelles LernenKünstliche IntellienzBildverarbeitungHyperspektralMatlab Deep LearningTensorflowONNXpytorchdeep learningEthereum (Solidity).
Machine Learning Engineer for Sensor Data and AI Applications
Summary
Machine learning expert with over 20 years of experience in public and industrial R&D, specializing in AI integration for technical devices. Proven skills in neural network deployment, machine learning automation, and securing AI models via blockchain.
- Core Competencies ML & AI Development: Skilled in Python, C/C++, Matlab, TensorFlow, ONNX, and PyTorch.
- Technical Deployment: Experience with TensorRT, ONNX, and TensorFlow Lite for technical applications.
- Automation & High-Performance Computing: Led ML SaaS projects, integrating infrastructures like AWS.
- SpecializationsSensor & Spectral Data Analysis: Expertise in hyperspectral imaging for precision agriculture, electronics, and personal care.
- Blockchain for AI Security: Secured models using smart contracts on platforms like Ethereum.
Experience & Education
Extensive project leadership in R&D, with a specialized degree in AI for engineering applications.
Sprachen
Englischverhandlungssicher
Projekthistorie
Problem:
Needed a secure, user-friendly web app that integrates ML for inference and data visualization, with access control and blockchain-enabled ownership of AI models.
Action:
Developed modules in Ionic, integrated AI inference in-browser with ONNX/WebAssembly and AWS Lambda, represented models as NFTs on Ethereum, secured access via user wallets, visualized inference results, and integrated with instrument control software for optical sensors.
Result:
Delivered a robust, multi-functional app that enabled flexible AI deployment, secure access, and innovative blockchain-based AI ownership. This solution improved user experience, expanded business possibilities, and positioned the project as a market leader.
Needed a secure, user-friendly web app that integrates ML for inference and data visualization, with access control and blockchain-enabled ownership of AI models.
Action:
Developed modules in Ionic, integrated AI inference in-browser with ONNX/WebAssembly and AWS Lambda, represented models as NFTs on Ethereum, secured access via user wallets, visualized inference results, and integrated with instrument control software for optical sensors.
Result:
Delivered a robust, multi-functional app that enabled flexible AI deployment, secure access, and innovative blockchain-based AI ownership. This solution improved user experience, expanded business possibilities, and positioned the project as a market leader.
Problem:
The client in the lubricant industry needed accurate forecasting of product properties for better quality control and predictive maintenance.
Action:
I developed a time-series forecasting model using TensorFlow and integrated sensor data with Node-RED for automated data collection and real-time inference, deploying on Azure Cloud. I also led the project technically and mentored a master’s student.
Result:
The project delivered a reliable model that improved forecasting accuracy, streamlined production, and provided actionable insights for the client.
The client in the lubricant industry needed accurate forecasting of product properties for better quality control and predictive maintenance.
Action:
I developed a time-series forecasting model using TensorFlow and integrated sensor data with Node-RED for automated data collection and real-time inference, deploying on Azure Cloud. I also led the project technically and mentored a master’s student.
Result:
The project delivered a reliable model that improved forecasting accuracy, streamlined production, and provided actionable insights for the client.
Problem:
Traditional grain quality control during harvest and processing lacks real-time precision, leading to inefficiencies.
Action:
Led the development of a sensor-based AI system using neural networks trained on spectral-optical measurements for real-time quality analysis. My role included model development, deployment, software rollout, and dashboard application creation.
Result:
The project enabled precise, real-time quality control, enhancing efficiency in grain processing.
Link: https://www.iffocus.online/echtzeit-analysen-fuer-die-getreideernte/
Traditional grain quality control during harvest and processing lacks real-time precision, leading to inefficiencies.
Action:
Led the development of a sensor-based AI system using neural networks trained on spectral-optical measurements for real-time quality analysis. My role included model development, deployment, software rollout, and dashboard application creation.
Result:
The project enabled precise, real-time quality control, enhancing efficiency in grain processing.
Link: https://www.iffocus.online/echtzeit-analysen-fuer-die-getreideernte/