Ebrahim Songhori
Founding Member Of Technical Staff at Google DeepMind
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolEbrahim Songhori is a Staff Research Engineer at Google DeepMind and a founding technical leader at Ricursive Intelligence with 11 years of experience building production ML and research systems. His career spans progressive engineering roles at Google—rising from internships to Senior Software Engineer—and now focuses on large-scale AI research and applied ML. He combines deep academic training (Ph.D. and M.Sc. in Electrical and Computer Engineering from Rice) with hands-on software and DevOps skills, evidenced by contributions to the widely used TensorFlow Agents library where he improved dependency management, fixed API deprecations, and strengthened testing and docs. Based in Mountain View, he also advises health-tech startups like Learnify Health, bridging research insights to product strategy. Colleagues describe him as someone who moves fluidly between research rigor and production reliability, often solving subtle integration and release issues that others overlook.
11 years of coding experience
7 years of employment as a software developer
University of California, San DiegoPh.D Electrical and Computer Engineering, Ph.D Electrical and Computer Engineering at Rice UniversityBachelor of Science Computer Engineering-Hardware, Bachelor of Science Computer Engineering-Hardware at University of Tehran
Persian, English
Github Skills (15)
keras10
tensorflow10
python10
cicd9
reinforcement-learning9
machine-learning9
algorithm9
cd9
algorithms9
unit-testing8
testing8
abtest8
ab-testing8
ui-testing8
bandit6
Programming languages (3)
Github contributions (5)
tensorflow/agents
Dec 2023 - Sep 2024
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
Role in this project:
ML Engineer & DevOps Engineer
ML Engineer & DevOps EngineerContributions:1 PR, 2 pushes, 1 branch in 9 months
Contributions summary:Ebrahim contributed to the TensorFlow Agents library by adding tf-keras as a dependency and then removing it, indicating an understanding of dependency management within a TensorFlow environment. They also fixed a bug related to deprecated keras.layers, demonstrating knowledge of TensorFlow and Keras APIs. Furthermore, the user updated documentation and made modifications to the testing infrastructure, showing a grasp of release procedures and testing frameworks.
scalabletf-agentsmultiagent-reinforcement-learningtensorflow-librarymulti-armed-bandits
esonghori/webpage-hugo
Feb 2015 - Jul 2017
Contributions:34 commits, 33 pushes in 2 years 5 months
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