Chen Sun
Machine Learning Engineer - Gemini at Google DeepMind
Mountain View, California, United States
Summary
👤
Senior🎓
Top SchoolChen Sun is a Machine Learning Engineer with a Ph.D. in Computer Science and 11 years of experience building large-scale ML data infrastructure and distributed systems. Currently at Google DeepMind improving quality of Gemini’s LLMs and deep generative models, he previously worked on asynchronous distributed deep learning and compilers for TPUs/GPUs at Google. At LinkedIn he helped develop the Machine Learning Feature Store and AI engineering platform (contributing to Feathr), blending production-grade engineering with ML research. His expertise spans Spark, parallelism, concurrency, and multi-threaded systems, as well as ML, NLP, and bioinformatics for large-scale genomic analysis and variant interpretation. Based in Mountain View, he brings together academic rigor and pragmatic system design to operationalize complex models at scale. A less obvious strength is his cross-domain fluency—translating bioinformatics algorithmic insights into scalable ML infrastructure and compiler optimizations.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at Penn State University
Chinese, English
Github Skills (23)
scoring10
matching10
bioinformatics10
package-management9
conda9
genome9
sequencing9
rna-seq9
genomics8
bioconda8
diagnostics8
datasets8
machine-learning6
windows4
wsl23
Programming languages (4)
Github contributions (5)
medvedevgroup/varmatch
May 2015 - Jan 2018
robust matching of small variant datasets using flexible scoring schemes
Contributions:149 commits, 4 PRs, 51 pushes in 2 years 8 months
scoringmatchingdatasetmachine-learningschemes
medvedevgroup/vargeno
Dec 2017 - Feb 2019
Towards fast and accurate SNP genotyping from whole genome sequencing data for bedside diagnostics.
Contributions:4 releases, 37 commits, 2 PRs in 1 year 1 month
whole-genome-sequencinggenomesequencing-datagenotypingsequencing
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