Ilya Philippov is a Senior Software Engineer with 13 years of experience building high-performance systems at the intersection of compilers, low-level networking, and large-scale ML infrastructure. He has led core projects at Intel—authoring the NFF-Go network function framework and contributing to the ISPC SPMD compiler—and later applied that systems expertise to latency-critical and quality-improvement work on Google Search LLMs. Currently at Google DeepMind, he bridges deep technical implementation with model quality evaluation, fine-tuning and inference optimization. His background combines a PhD in Computer Science from MIPT with hands-on experience where Go, DPDK, LLVM and performance profiling meet production ML. Notably, he designed automated multithreaded scaling and ordering heuristics for packet processing and implemented compiler-level optimizations across multiple instruction sets. Based in Austin with Swiss roots, he brings a rare blend of low-level engineering rigor and practical ML product impact.
12 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Moscow Institute of Physics and Technology (State University) (MIPT)
NFF-Go -Network Function Framework for GO (former YANFF)
Role in this project:
Back-end Developer
Contributions:1 release, 308 commits, 279 PRs in 2 years 1 month
Contributions summary:Ilya primarily contributed to the `aregm/nff-go` repository, a network function framework, by implementing and testing functionalities within the packet processing module. They added new functions for packet encapsulation, decapsulation, and byte manipulation, enhancing the core packet handling capabilities. The user also made improvements to existing functions, including bug fixes, type corrections, and test additions to ensure functionality and correctness. These contributions demonstrate expertise in low-level networking and the Go programming language.
Contributions summary:Ilya contributed to the Intel® Implicit SPMD Program Compiler, specifically focusing on compiler features and optimization. They implemented support for the `createFunction()` method with a `DICompositeType` argument, as well as added and improved support for skipping tests and added support for time output. They also made changes to a function related to vector flattening and performed several other code updates that improve performance.
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Ilya Philippov - Senior Software Engineer at Google DeepMind