Summary
Eliot Ayache is a tech lead and senior ML engineer with a PhD in computational astrophysics and nine years of experience translating advanced numerical simulation and statistical methods into production ML systems. He has led R&D product architecture and delivery at startups and industry (Aris Machina, Northvolt), building explainable AI, agentic GenAI systems, and cloud-native MLOps that cut experimental latency and improved traceability in battery R&D. Comfortable across HPC, C++/Fortran simulation stacks and modern ML tooling, he bridges research rigor with product-minded engineering to move proofs-of-concept into scalable platforms. Notably, his background in astrophysical hydrodynamics and bespoke solver development informs novel approaches to time-series and root-cause analysis in greentech applications. He thrives in interdisciplinary teams and regularly communicates complex methods to both specialists and non-experts, running internal seminar series and leading academic collaborations.
9 years of coding experience
6 years of employment as a software developer
Preparatory Classes, Ranked 79th out of 3489 at the Mines-Ponts national competitive examination, Preparatory Classes, Ranked 79th out of 3489 at the Mines-Ponts national competitive examination at Lycée Saint-Louis - Paris
Doctor of Philosophy - PhD, Computational Astrophysics, Doctor of Philosophy - PhD, Computational Astrophysics at University of Bath
Master of Science - MS, Astronomy and Astrophysics - Astronomy, Astrophysics and Space Engineering (AAIS) (M1, M2), Master of Science - MS, Astronomy and Astrophysics - Astronomy, Astrophysics and Space Engineering (AAIS) (M1, M2) at PSL Research University
Master of Science - MS (diplôme d'ingénieur), Applied Mathematics and Physics, Master of Science - MS (diplôme d'ingénieur), Applied Mathematics and Physics at Mines Paris
French, English, Spanish, Swedish