Jan-christoph Klie
Applied Scientist at Klie AI
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolJan-christoph Klie is an applied scientist and machine learning engineer with a PhD in NLP and 13 years of experience building ML systems, backend infrastructure, and annotation tools. He combines hands-on expertise in GenAI/LLMs/RAG, data annotation workflows, and AI IT infrastructure with production experience at Apple and now Amazon, while running his own AI consultancy. His contributions to the INCEpTION semantic annotation platform highlight a pragmatic focus on core backend functionality and robust testable features. Comfortable across research and engineering, he bridges interactive ML research (semantic parsing, SRL, continual learning) with scalable software delivery. Based in Berlin, he also brings a long-standing interest in robotics, compilers and language learning—he studies Chinese in his spare time.
13 years of coding experience
1 year of employment as a software developer
Bachelor's Degree, Applied Computer Science, Bachelor's Degree, Applied Computer Science at Baden-Wuerttemberg Cooperative State University MannheimMarketing, Marketing at Anglia Ruskin UniversityTechnischen Universität DarmstadtChinese, Chinese at Keats Chinese School
German, English, Chinese
Stackoverflow
4,064reputation
576kreached
56answers
24questions
intellij-idea
top-5%
logical-operators
top-5%
Github Skills (12)
unit-testing10
javas10
java10
intellij-idea9
logical-operators9
test-driven-design9
command-line-arguments6
argparse6
docopt6
syntax6
jackson6
python6
Programming languages (16)
Github contributions (5)
inception-project/inception
Apr 2018 - Jan 2023
INCEpTION provides a semantic annotation platform offering intelligent annotation assistance and knowledge management.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 releases, 100 reviews, 549 commits in 4 years 10 months
Contributions summary:Jan-christoph's contributions focused on enhancing the knowledge base backend. They implemented support for qualifiers within the knowledge base, including setting up test infrastructure and performing checks to ensure functionality. Their work involved modifying Java code related to the knowledge base service and the supporting test fixtures. These contributions suggest a focus on core functionality and the verification of new features.
semanticactive-learningknowledgeentity-linkingassistance
jcklie/dotfiles
Sep 2018 - Aug 2021
Contributions:34 commits, 20 pushes in 2 years 10 months
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