Summary
Aleksandr Efremov is a researcher and senior C++ programmer with 11 years of experience building high-performance systems across AI, quant trading, and scientific computing. Based in San Francisco, he has contributed to and led work on state-of-the-art language models at OpenAI (including GPT-5 and the GPT-5.4 nano release) and developed algorithmic research and AI labs at Hudson River Trading. His background spans brain–machine interfaces at Neuralink, automatic differentiation for C++ at CERN, and deep learning systems at Google Brain, blending low-level systems expertise with ML research. He is comfortable shipping production-grade backend and networking code, designing software architectures, and applying game-development techniques to complex problems. Notably, his early work integrated Clad into CERN’s ROOT framework, replacing numerical differentiation in high-performance scientific workflows.
11 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Faculty of Information Technology CTU in Prague
Master's degree, Neural Systems & Computation, Master's degree, Neural Systems & Computation at ETH Zürich
English, Russian, Czech