Mubarak Seyed
Machine Learning Engineer at Apple
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolMubarak Seyed is a seasoned machine learning engineer and engineering leader based in San Francisco with 13+ years of experience building scalable AI systems. He currently leads distributed training of deep learning models and large-scale ML infrastructure at Apple, focusing on performance and reliability in production. Previously, as Engineering Lead for Siri Natural Language and Machine Learning Platform, he designed scalable ML services, high-performance runtime inference, and distributed architectures powering NLP and voice features. He is an active open-source contributor and Apache Flume committer, with hands-on experience across Layer, Siri Core Platform, and Apple’s data infrastructure, including work on data replication, caching, and distributed systems. His open-source contributions extend to Alluxio, where he improved data handling and network communication robustness, reflecting a strong systems mindset. He holds Stanford Graduate Certificate in AI (2023) and Advanced Computer Security Certification, along with a B.E from Madurai Kamaraj University, underscoring a blend of ML, security, and enterprise-scale engineering.
13 years of coding experience
12 years of employment as a software developer
B.E, B.E at Madurai Kamaraj UniversityAdvanced Computer Security Certification, Computer Security, Advanced Computer Security Certification, Computer Security at Stanford University
Github Skills (14)
javas10
data-handling10
alluxio10
java10
networking9
communications9
documentation9
data-communication9
file-management9
network9
net9
documentations9
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
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.