Víctor Jiménez Rodríguez
Machine learning research engineer • Zurich, Switzerland
About
Machine learning research engineer with a background in physics and statistics, and a proven track record in both academic and industrial environments. Interested in the assessment and understanding of robustness in machine learning systems. Currently building advanced knowledge representations for high-risk, technical domains and the algorithms and agentic systems that navigate them.
Experience
Founding Research Engineer at Uthereal
Designed and deployed an end-to-end agentic RAG pipeline for expert-level technical documents in high-risk domains. Built an experimental evaluation framework to assess model robustness and system reliability.
Scientific Assistant at Institute for Machine Learning (ETH)
Led and contributed to multiple R&D projects integrating A-RAG pipelines in the medical domain. Worked across research and engineering stakeholders.
Scientific Assistant at Institute for Machine Learning (ETH)
Conducted research focused on the derivation of finite-sample robustness guarantees in high-dimensional compositional settings.
Research Intern at Institute for Machine Learning (ETH)
Completed master's thesis on improving robustness of deep learning models through posterior agreement based model selection. Manuscript published in TMLR.
Research Trainee at Department of Physics (TUM)
Conducted bachelor's thesis on EIS characterization of lithiated TiO2-coated LICGC electrolytes. Contributed to published work.