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Location: Munich, Germany Remote: Yes Willing to relocate: Yes Technologies: Python (PyTorch, TensorFlow), Reinforcement Learning, Medical Imaging, Machine Unlearning, Physics-informed ML, Quantum Computing, Protein Structure Prediction, NLP, Java, SQL Résumé/CV: https://drive.google.com/file/d/1b9UfeqFvEu0t4sTGNd8yiJ1m60x... Email: essence_mallard.5a@icloud.com Hi, Kilian here :) ML engineer / research-minded generalist with a recent M.Sc. in Informatics from TUM, including a thesis on machine unlearning in medical imaging (@Harvard Medical School). I’ve worked on problems like reinforcement learning for tumor landmark detection in MRI, and deep learning for physical systems and protein structure prediction. I like forming own ideas and following them through — from literature review to implementation, evaluation, and iteration. I can reproduce papers, fine-tune models, explore new methods, and design experiments that actually test hypotheses. I’m especially motivated by early-stage work that blends research thinking with practical engineering. In team settings, I tend to gravitate toward coordination and planning roles, and outside of work, I’ve led a 300+ member volleyball department for several years — which taught me how to manage people, not just models. I'm looking for roles at the intersection of research and engineering, eg early-stage AI projects where curiosity, ownership, technical depth matter and impact-driven development are valued. |