Over Marco
Duits
Tweetalig / moedertaal
Engels
Vloeiend
Roemeens
Tweetalig / moedertaal
Werkervaring
- Keyspot AISenior Machine Learning EngineerCONSULTANCY & AUDITINGnovember 2024 - Vandaag (1 jaar en 7 maanden)Berlin, Duitsland
- Developed an automated document revision detection tool for rapid identification of modifications in technical RFQ/RFP documents, greatly reducing manual verification time.
- Created a multimodal model for precise data extraction from complex datasheets, streamlining the preparation of bids and proposals.
- Implemented a hierarchical retrieval-augmented chatbot system for semantic understanding and accurate response generation, optimized to minimize false-positive retrieval.
- Delivered automated risk detection algorithms that efficiently screen RFQ/RFP documents for compliance risks, enabling quick decision-making via an intuitive dashboard interface.
- Siemens AGMachine Learning EngineerONDERZOEKSCENTRAapril 2022 - oktober 2024 (2 jaren en 7 maanden)Berlin, Duitsland
- Engineered a retrieval-augmented generation pipeline incorporating hierarchical retrieval and context refinement for improved accuracy and reliability.
- Created metrics for assessing context relevance and detecting hallucinations to enhance the quality and trustworthiness of AI outputs.
- Developed novel unsupervised algorithms for semantic segmentation of text documents, supporting efficient content analysis (patent pending).
- Built a multimodal encoder-decoder architecture integrating knowledge graphs for enhanced language modeling and data representation, reducing hallucinations in accuracy-critical business settings.
- Designed a context-aware recommendation system for question generation tailored to technical documentation.
- Siemens AdvantaMachine Learning EngineerCONSULTANCY & AUDITINGnovember 2020 - maart 2022 (1 jaar en 5 maanden)Munich, Duitsland
- Built and deployed an extractive semantic search engine using advanced retrieval and reranking techniques.
- Fine-tuned transformer-based machine learning models (TSDAE, MLM, CT, SimCSE) for precise domain adaptation on proprietary datasets.
- Implemented comprehensive MLOps practices for efficient experiment management and deployment.
- Developed a production-grade web application using FastAPI, Docker, and Angular, delivering intuitive user interaction aligned with corporate visual standards.
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Opleidingen
- Master of ScienceLMU München2024Informatik
- Bachelor of ScienceLMU München2021Informatik