René Schönfelder
Solutions Architect at Nebius
Hamburg, Germany
Summary
👤
Senior🎓
Top SchoolRené Schönfelder is a Solutions Architect and Deep Learning Engineer based in Hamburg with 11 years of experience building cloud-native ML systems for life sciences, energy and media. He combines hands-on model development—PEFT/LoRA, RLHF, prompt engineering and GenAI with satellite data—with production-focused MLOps on multinode GPU clusters and major cloud platforms. René has a strong track record delivering time-series forecasting for renewables, scaling ML workloads at Siemens and media groups, and making medical devices smart through AWS architectures. He blends research roots from a master's in Robotics, Cognition & Intelligence at TUM with pragmatic engineering, often bridging model experimentation and production deployment. Notably he moves between low-level GPU training orchestration and high-level prompt/program-aided approaches, enabling efficient model fine-tuning at scale.
11 years of coding experience
11 years of employment as a software developer
Master's Degree, Robotics, Cognition, Intelligence, Master's Degree, Robotics, Cognition, Intelligence at Technical University Munich
English, German, Spanish
Github Skills (14)
predict8
electric-vehicles7
routes7
redmine7
energy7
modularity5
frontend4
visualization4
webapp4
polymer3
ruby3
react3
vue2
javascript2
Programming languages (2)
Github contributions (5)
schoenfr/schoenfr.github.io
Apr 2016 - Jun 2016
Contributions:83 pushes, 1 branch in 1 month
schoenfr/webapp
Sep 2015 - Feb 2016
Contributions:4 PRs, 13 pushes in 4 months
polymer-componentswebapppolymernavigation
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