Till Döhmen - AI Lead at MotherDuck

Till Döhmen

AI Lead at MotherDuck

Amsterdam, North Holland, Netherlands

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Summary

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Rockstar

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Top School

Till Döhmen is an AI Lead based in Amsterdam with 11 years of experience building data-intensive ML systems at the intersection of data management and applied research. He has driven production-focused feature store and MLOps work—contributing backend improvements to the well-known Hopsworks platform—while leading AI efforts at startups and research institutes. His background spans hands-on engineering in Java, Spark and Python to architecting scalable ML pipelines and feature engineering frameworks for real-world recommender and analytics systems. As a former Fraunhofer team co-lead and research engineer, he blends academic rigor (PhD candidacy in Databases and Information Systems) with pragmatic delivery in industry. He’s comfortable moving between low-level data plumbing and higher-level ML productization, and maintains an active open portfolio of research and tooling on his personal site. Colleagues describe him as a developer-researcher who elevates ML reliability through principled data management.

11 years of coding experience

12 years of employment as a software developer

Bachelor’s Degree, Scientific Programming, Bachelor’s Degree, Scientific Programming at Aachen University of Applied Sciences - FH Aachen

Master’s Degree, Artificial Intelligence, Data Science Specialization, Master’s Degree, Artificial Intelligence, Data Science Specialization at Vrije Universiteit Amsterdam (VU Amsterdam)

Guest Researcher, INtelligent Data Engineering Lab (INDE Lab), Guest Researcher, INtelligent Data Engineering Lab (INDE Lab) at University of Amsterdam

PhD Candidate, Databases and Information Systems, PhD Candidate, Databases and Information Systems at RWTH Aachen University

Dutch, French, English, German

Github Skills (8)

javas10

feature-store10

feature-engineering10

java10

sql6

machine-learning4

data-science4

python4

Programming languages (9)

JavaC++ShellScalaJavaScriptHTMLJupyter NotebookRuby

Github contributions (5)

logicalclocks/hopsworks

Aug 2021 - Dec 2022

Hopsworks - Data-Intensive AI platform with a Feature Store

Role in this project:

Back-end Developer

Contributions:5 reviews, 5 commits, 7 PRs in 1 year 3 months

Contributions summary:Till primarily focused on improving the Hopsworks platform's feature store functionalities. They contributed to optimizing data profiling and statistics configurations, specifically related to feature groups, training datasets, and time travel features. The changes involved modifying Java code related to statistics configurations and partition key validations. Additionally, the user addressed API normalization for reading changes based on commit time and refactored transformation function output types.

gcppythonserverlessai-platformhopsworks

tdoehmen/feature-store-api

Jul 2021 - Aug 2023

Python - Java/Scala API for the Hopsworks feature store

Contributions:27 PRs, 367 pushes, 70 branches in 2 years 1 month

apipythonhopsworksscalafeature-store

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