Miriam Kuemmel

Team Lead Solution Engineering at deepset

Miriam Kuemmel has worked in a variety of roles since 2017. In 2017, they were a Teaching and Research Assistant - Python and an IT Department Assistant at Universität Konstanz. In 2018, they were a Research Scholar at the University of Massachusetts Amherst, where they conducted research on sluicing and developed an algorithm in Python to automatically extract sluicing instances from a corpus. Miriam was also a Chatbot Development Intern at Daimler AG during the same year. In 2019, they were a Data Scientist at DEMOS Gesellschaft für E-Partizipation mbH - Agile Tools for Open Societies. In 2021, they were a Data Scientist at Xircle. Currently, they are an Applied NLP Engineer at deepset, providing the link between cutting-edge NLP research, deepset's framework Haystack, and the needs of clients. Miriam is also responsible for empowering and enabling customers to build semantic search and QA applications, providing guidance and technical implementation work, as well as data science insights.

Miriam Kuemmel attended the University of Massachusetts Amherst from 2018 to 2019 as a research visitor. From 2016 to 2019, they attended the University of Konstanz, where they obtained a Master of Arts degree in Speech and Language Processing. Prior to that, they attended FAU Erlangen-Nürnberg from 2012 to 2015, where they obtained a Bachelor of Arts degree in German Literature and Linguistics.

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Berlin, Germany

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deepset

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Deepset is building the next enterprise search engine fueled by NLP and open-source. Building on top of latest NLP research they leverage question answering & transfer learning to provide granular, semantic search results tailored to your domain.


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Headquarters

Berlin, Germany

Employees

51-200

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