Jonathan Clark
Research Scientist at Google
Greater Seattle Area United States
Summary
👤
Senior🎓
Top SchoolJonathan Clark is a research scientist with 15 years of experience specializing in multilingual machine learning and neural machine translation, currently working on multilinguality for Google's Gemini. He previously led core translation efforts at Microsoft Translator and built production training infrastructure at Safaba (now part of Amazon), shipping features that powered Bing, Skype, and custom translator services. A Carnegie Mellon PhD in Language Technologies, he combines deep academic grounding with hands-on systems and performance engineering—evidenced by contributions to high-profile open-source projects like Moses and KenLM. His work spans model research, optimization, and reliable deployment, with a knack for squeezing performance and observability out of language-model pipelines. Based in the Greater Seattle Area, he keeps active in open-source artifacts from his grad-school era while driving industry-scale multilingual systems. Colleagues describe him as someone who bridges research rigor and production practicality, often surfacing subtle engineering gains such as precise timing and memory-use estimates that improve real-world translation workflows.
15 years of coding experience
8 years of employment as a software developer
BS, Computer Science, Mathematics, BS, Computer Science, Mathematics at Texas Christian UniversityMaster of Science (MS), Language Technologies, Computer Science, Master of Science (MS), Language Technologies, Computer Science at Carnegie Mellon University
Stackoverflow
2,523reputation
823kreached
16answers
2questions
gcc
top-5%
assert
top-5%
Github Skills (28)
algorithm10
algorithms10
machine-translation10
c-language10
data-structure10
performance-optimization10
language-modeling10
data-structures10
cprogramming-language10
gcc9
build-system9
stacktrace9
computer-engineering9
assert9
file-handling8
Programming languages (5)
Github contributions (5)
kpu/kenlm
Nov 2012 - Dec 2012
KenLM: Faster and Smaller Language Model Queries
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:21 commits in 1 month
Contributions summary:Jonathan contributed to the KenLM project by implementing and modifying core functionalities related to language model building and optimization. They added timing information to the build process and provided size estimates for memory usage, aiding in performance analysis. Their work involved changes in the build pipeline, sorting algorithms, and ARPA file writing, indicating a focus on optimizing the language model's performance and memory footprint. Furthermore, the user addressed merge conflicts and fixed error messages within the codebase.
nlplanguage-modelsmallerkenlmfaster
moses-smt/mosesdecoder
Apr 2012 - Sep 2012
Moses, the machine translation system
Role in this project:Back-end Developer
Back-end DeveloperContributions:9 commits in 4 months
Contributions summary:Jonathan's contributions focused on enhancing the Moses machine translation system. They modified the code to include phrase segmentation information in the n-best list output, improving the reporting of translation results. The changes involved modifying `IOWrapper.cpp` and `Main.cpp` to incorporate this new functionality. They also updated the timer class for more precise timing on systems supporting `CLOCK_MONOTONIC`.
i18nmachine-translationtranslationlocalizationmoses
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