Raphael Mitsch
AI Team Lead at Climatiq
Vienna, Austria
Summary
🤩
Rockstar🎓
Top SchoolRaphael Mitsch is an AI team lead based in Vienna with 11 years of experience building production-grade ML and NLP systems for high-stakes domains like carbon accounting and human rights. He specializes in making LLMs and retrieval pipelines reliable, traceable, and defensible so they withstand audits, regulators, and real-world failure modes rather than just demos. At Climatiq he directs technical strategy for agentic pipelines, embeddings, and confidence scoring, and previously engineered core search, recommendation, and deployment features for carbon intelligence. His open-source track record includes substantive contributions to spaCy—overhauling entity linking and helping integrate LLMs via spacy-llm—which underscores his focus on robust, practical NLP. Raphael pairs strong research awareness with hands-on system design across data pipelines, evaluation, and governance, and brings a rare emphasis on auditability to applied AI. He combines a Data Science master’s with broad engineering roots, enabling both strategic leadership and deep implementation.
11 years of coding experience
15 years of employment as a software developer
Master’s Degree, Data Science, Master’s Degree, Data Science at University of ViennaEngineer’s Degree, Computer Science, Engineer’s Degree, Computer Science at HTBLVA Spengergasse
German, English, Spanish
Github Skills (10)
error-handling10
nlp10
spacy10
python10
natural-language-processing10
cython10
testing9
cli9
artificial-intelligence8
machine-learning8
Programming languages (7)
Github contributions (5)
explosion/spaCy
Apr 2022 - Jan 2023
💫 Industrial-strength Natural Language Processing (NLP) in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:409 reviews, 20 commits, 99 PRs in 9 months
Contributions summary:Raphael primarily refactored error messages within the spaCy library to remove hardcoded strings and utilize custom error messages. This involved modifying code across multiple files, including those related to the edit trees, token graphs, and span objects, and implementing these changes in the spacy/errors.py and spacy/ml/parser_model.pyx. The user also worked on allowing optional assets in the spacy project, including refactoring CLI commands, adding documentation, and implementing project config tests. Moreover, they integrated changes related to the entity linking functionality.
fairness-mlpythondata-preprocessinglanguage-processingtokenization
LDAforVisProject/LDA
Sep 2014 - Jun 2016
Contributions:36 commits, 18 pushes, 1 branch in 1 year 9 months
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