Martin Maas
Mountain View, California, United States
Summary
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SeniorMartin Maas is a Staff Research Scientist at Google DeepMind, where he focuses on applying machine learning to systems problems and shaping the next generation of AI-enabled architectures. He earned his PhD at UC Berkeley and has a broad research footprint spanning managed language runtimes, operating systems, and computer architecture, with a full-stack perspective from hardware to programming systems. In addition to his academic work, he contributed extensively to Google’s tcmalloc, adding telemetry features, refining time-series tracking, and improving memory-management observability. His career blends warehouse-scale systems work, RTL-level hardware insight, and production-grade software engineering, reflecting a knack for turning complex requirements into robust, scalable solutions. A standout early competitor, he represented Germany in the IOI and ISEF, illustrating a long-standing drive for excellence. Based in Mountain View, California, he continues to lead research that bridges AI and systems at scale.
11 years of coding experience
Github Skills (22)
c-language10
performance-monitor10
memory-management10
performanceanalysis10
performance-measurement10
performance-analysis10
performanceanalytics10
performance-tuning10
performance-monitoring10
performancemonitor10
c-programming-language10
datastructures9
datastructure9
data-structure9
algorithm9
Programming languages (9)
Github contributions (5)
google/tcmalloc
Feb 2020 - Feb 2022
Role in this project:
Back-end Developer
Back-end DeveloperContributions:21 commits in 2 years
Contributions summary:Martin made multiple contributions focused on refactoring and extending the time series tracking functionality within the TCMalloc library. Their work involved the creation of new telemetry features and the refactoring of existing code to eliminate duplication and improve maintainability. The user also implemented additional telemetry for the `HugePageFiller` to capture metrics related to page usage and fragmentation over time, contributing to a deeper understanding of memory management. Further contributions include refactoring and optimization related to the clock and object lifetime tracking within TCMalloc.
riscv/riscv-j-extension
Apr 2020 - Dec 2022
Working Draft of the RISC-V J Extension Specification
Contributions:4 releases, 5 reviews, 15 commits in 2 years 8 months
risc-vriscspecificationjit
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