Edgar Liberis is a Quantitative Researcher & Developer with 11 years of experience, blending deep learning research and production engineering from Cambridge to high-frequency trading at Jump Trading. Currently a PhD candidate at the University of Cambridge, he focuses on neural network performance optimisation and brings that rigor to low-latency, data-driven trading systems. His background includes applied ML roles at PolyAI and Featurespace, where he developed low-data NLP techniques and fraud-detection models while also accelerating engineering tooling. Early experience at Jane Street honed his systems and language-level skills, including contributions to OCaml compiler enhancements. Edgar combines academic depth with pragmatic delivery—translating research ideas into performant, production-ready code for demanding, real-time environments. He is based in Cambridge and known for bridging theoretical ML advances with engineering constraints that matter in trading and fraud detection.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Oxford
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Cambridge
Contributions:24 commits, 1 PR, 23 pushes in 2 years 6 months
memorytensorboardoptimizertensorflowanalyzer
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Edgar Liberis - Quantitative Researcher & Developer