Vadim Skipin is a Principal Software Engineer with 14 years of experience building high-performance, cloud-scale systems and storage platforms, now based in Berlin and currently at ClickHouse. He has led engineering efforts at AWS (Aurora and Redshift Zero-ETL) and Yandex, where he launched foundational projects like Network Block Store/Network File Store and a real-time stream processing framework powering search at massive scale. Vadim combines deep systems and full-stack optimization expertise (C++, Go, Python) with hands-on DevOps work—evidenced by ARM64 performance and build-system improvements contributed to the widely used CatBoost library. Known for reducing latency and scaling reliable infrastructure, he brings both architectural vision and the pragmatic skill to ship and tune distributed services. An endurance athlete as well (Sub10 Ironman), he pairs long-term stamina with relentless focus on performance and reliability.
14 years of coding experience
26 years of employment as a software developer
Applied Math, Applied Math at Saint Petersburg State University
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Role in this project:
Back-end & DevOps Engineer
Contributions:12 commits in 4 years 1 month
Contributions summary:Vadim's contributions primarily focused on integrating and optimizing the CatBoost library for ARM64 architecture. They worked on adapting the library's build system, specifically the `ya.make` files, for ARM64 environments. Furthermore, the user updated dependencies related to Infiniband drivers, likely to support high-performance networking, and addressed spinlock performance on ARM64. These changes suggest a focus on optimizing the library's performance and compatibility across different hardware platforms.
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Vadim Skipin - Principal Software Engineer at ClickHouse