Summary
Leonid Alekseyev is a senior software engineer in San Francisco with 16 years of experience applying big-data, numerical computing, and machine learning techniques to production systems. He blends a strong applied-math and physics background (PhD-level optical physics) with hands-on engineering across backend services, data pipelines, and deployment, recently joining Meta after leading engineering at an enterprise blockchain startup. His career spans quantitative finance, terabyte-scale analytics, anomaly detection at Splunk, and building ML infrastructure for learning platforms—demonstrating comfort moving between research-grade simulations and pragmatic business logic. Notably, he pairs theoretical expertise in nano-optics and metamaterials with practical skills in Python, R, C++, and the Hadoop ecosystem, making him adept at turning complex models into scalable, operational software.
16 years of coding experience
14 years of employment as a software developer
MS, Electrical Engineering, MS, Electrical Engineering at Stanford University
Ph.D., Electrical Engineering (Optical Physics), Ph.D., Electrical Engineering (Optical Physics) at Princeton University
English, Russian