Brighton Muffat is a research engineer based in Paris with eight years of experience at the intersection of machine learning, computer science and quantitative finance. At Murex he accelerated calibration of option pricing models using deep learning, built an internal Python library for differential machine learning, and integrated optimized neural nets into a C++ quantitative library with low-level CPU tuning. His background combines a strong theoretical foundation from Ensimag and EPFL in financial engineering with hands-on quant and execution experience from internships and a fintech student co-founder role. He routinely translates cutting-edge research into production-ready systems and runs internal trainings to upskill colleagues in neural networks. Notably, he blends finance domain intuition with practical ML engineering—shipping optimized inference in a latency-sensitive production environment.
8 years of coding experience
1 year of employment as a software developer
Baccalauréat with major in maths and physics, Highest honours (18.18/20), Baccalauréat with major in maths and physics, Highest honours (18.18/20) at Lycée Fénelon
Contributions:6 commits, 14 pushes, 1 branch in 18 days
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