Mubarak Seyed
Machine Learning Engineer at The Apache Software Foundation
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolMubarak Seyed is a Machine Learning Engineer and engineering leader based in San Francisco with 13 years of experience building large-scale distributed systems and ML infrastructure at Apple. He has led Siri’s NLU and machine learning platform work, owning feature engineering, model serving, high-performance inference runtimes, and cross-DC data replication to support production ML at scale. Currently focused on distributed training of deep learning models and large-scale ML systems, he blends systems-level reliability work with applied AI research. An open-source committer to Apache Flume and contributor to Alluxio, he brings practical experience hardening data orchestration and networked I/O for analytics and ML workloads. Mubarak pairs hands-on engineering (Java, Netty, large-data stacks) with recent formal study in AI and advanced computer security from Stanford, underscoring his commitment to both cutting-edge models and robust, secure platforms. Colleagues rely on him for architecting scalable services that bridge low-level performance engineering and production ML delivery.
13 years of coding experience
12 years of employment as a software developer
B.E, B.E at Madurai Kamaraj UniversityGraduate Certificate, Artificial Intelligence, Graduate Certificate, Artificial Intelligence at Stanford University
Github Skills (13)
javas10
data-handling10
alluxio10
java10
networking9
communications9
documentation9
data-communication9
file-management9
network9
net9
orchestration8
orchestrate8
Programming languages (3)
Github contributions (5)
Alluxio/alluxio
Jul 2014 - Aug 2014
Alluxio, data orchestration for analytics and machine learning in the cloud
Role in this project:
Back-end Developer
Back-end DeveloperContributions:15 commits in 1 month
Contributions summary:Mubarak's commits primarily focus on enhancing the codebase through the addition of comprehensive Java documentation (Javadoc) for core classes like `MasterWorkerInfo`, `Users`, and `TachyonFile`. They also made changes related to data retrieval, including modifying the `DataServerMessage` and `RemoteBlockInStream` classes, indicating work on data handling and network communication within the Alluxio ecosystem. Further contributions involved addressing file handle leaks, and master image management, indicating a focus on improving the system's stability and robustness.
data-analysisvirtual-distributed-filesystemanalyticsorchestrationdata-science
layerhq/socko
Feb 2015 - Apr 2015
Contributions:24 PRs, 17 pushes, 17 branches in 1 month
web-servernetworkingscalanettyakka
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