Mohsen Akbari is a Staff Software Engineer in Irvine, CA with eight years of experience building high-performance systems across C/C++, Java, and Python, and a strong foundation in algorithms, OOP, machine learning, and signal/image processing. He currently leads the Core Data Storage team for Meta’s Modern Recommendation System, driving scalable storage and recovery features for latency-critical services. Previously he contributed to electronic trading and transaction infrastructure at Goldman Sachs and Bloomberg, and to Windows graphics kernel drivers at AMD, giving him deep cross-domain expertise from low-level drivers to distributed services. On GitHub he helped harden Facebook’s CacheLib—adding memory-safety checks, TTL/persistence features, and multi-threaded recovery—demonstrating practical impact on a widely used caching engine. He holds advanced degrees in electrical engineering and has a research background in sparse representations, which informs his applied work at the intersection of ML and systems. Known for shipping robust, production-first solutions, he blends kernel-level rigor with large-scale distributed system design.
7 years of coding experience
8 years of employment as a software developer
PhD, Electrical Engineering, PhD, Electrical Engineering at McGill University
Amirkabir University of Technology
M.Sc, Electrical Engineering, M.Sc, Electrical Engineering at Sharif University of Technology
Pluggable in-process caching engine to build and scale high performance services
Role in this project:
Back-end Developer
Contributions:10 commits in 11 months
Contributions summary:Mohsen primarily focused on improving the `cachelib` project's functionality and stability. Their contributions include addressing memory allocation issues by adding checks and migrating to `std::unordered_map`, enhancing object cache persistence by incorporating TTL and creation time, and introducing a timeout option for cache recovery. Furthermore, the user worked on multi-threaded persistence and recovery mechanisms to optimize cache operations.
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