Markus Rosenfelder
Head Of AI Strategy
Stuttgart, Baden-Württemberg, Germany
Summary
👤
Senior🎓
Top SchoolMarkus Rosenfelder is Head of AI Strategy with a decade of experience building production-ready ML systems that process large text corpora and deploy transformer models at scale. He blends a strong academic background—a summa cum laude PhD in Wirtschaftsinformatik—with hands-on expertise in GCP, Kubeflow, Kubernetes and GitLab CI/CD to operationalize research into reliable MLOps pipelines. His career spans university research and applied roles across startups and industry, including ML engineering at bits&birds and consulting on environmental AI projects, demonstrating an ability to translate domain science into scalable solutions. Pragmatic and research-driven, he often bridges the gap between exploratory modelling and robust deployment, ensuring models move from prototype to production in enterprise contexts.
10 years of coding experience
5 years of employment as a software developer
Master of Science - MS, Economics, Master of Science - MS, Economics at Albert-Ludwigs-Universität Freiburg im BreisgauDoctor of Philosophy - PhD, Wirtschaftsinformatik, Summa cum laude, Doctor of Philosophy - PhD, Wirtschaftsinformatik, Summa cum laude at Albert-Ludwigs-Universität Freiburg
English, German
Stackoverflow
126reputation
4kreached
7answers
2questions
Github Skills (41)
transfer-learning10
data-science9
webscraper9
artificial-intelligence9
pytorch9
python9
machine-learning9
pytorch-lightning9
simulations9
ai9
deep-learning9
keras9
efficientnet9
graph-neural-network9
graph-convolutional-networks9
Programming languages (2)
Github contributions (5)
MarkusRosen/pytorch_multi_input_example
Dec 2020 - Dec 2022
Multi-Input Deep Neural Networks with PyTorch-Lightning - Combine Image and Tabular Data
Contributions:1 review, 21 commits, 19 PRs in 2 years
deep-neural-networkspytorch-lightningpytorchtabular-data
MarkusRosen/keras-efficientnet-regression
Sep 2020 - Nov 2022
Apply transfer learning of EfficientNet to a custom regression problem with Keras and TensorFlow 2.
Contributions:1 review, 14 commits, 8 PRs in 2 years 2 months
efficientnetkerastensorflowtransfer-learningdeep-learning
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