Amr Kayid is an AI researcher-engineer with a decade of experience building and scaling intelligent systems across industry and academia, from Cohere’s 100B+ LLM training pipelines to generative world models at Runway. He blends deep research (reinforcement learning, affective/emotional AI, quantum ML exposure) with production expertise in distributed training, JAX/TPU stacks, and infrastructure as code. Early-stage and growth-stage experience includes helping Cohere scale engineering and evaluation frameworks, while open-source contributions (notably CI/CD and Terraform work for OpenMined/PySyft) show a focus on reproducibility and secure, privacy-preserving ML. Amr’s background spans applied robotics, BCI signal processing, and autonomous driving research, giving him a knack for multimodal systems that link perception to action. Based in Old Toronto, he favors building systems that are not only capable at scale but also emotionally aware and ethically grounded. A less obvious thread through his career is a consistent emphasis on tooling and developer experience—automating workflows that make cutting-edge research practical to ship.
9 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Computer Science Engineering, Bachelor's degree, Computer Science Engineering at The German University in Cairo
QRL Researcher, Quantum Machine Learning and Tensor Networks, QRL Researcher, Quantum Machine Learning and Tensor Networks at Max Planck Society
Master's degree, Data Engineering and Analytics - Onhold, Master's degree, Data Engineering and Analytics - Onhold at Technical University of Munich
Thanaweya Amma, Mathematics, Thanaweya Amma, Mathematics at Omar Ibn El Khatab Secondary School
Perform data science on data that remains in someone else's server
Role in this project:
DevOps Engineer
Contributions:79 commits in 9 months
Contributions summary:Amr primarily contributed to the project by automating code formatting, style checks, and CI/CD processes. Their work involved integrating tools like `yapf`, `isort`, and `black` for code quality and consistency. They also configured GitHub Actions for automated testing and formatting, demonstrating a focus on improving the development workflow and code maintainability within the `openmined/pysyft` repository. Further contributions include deployment setup using Terraform, demonstrating experience with infrastructure as code and cloud deployment.
Contributions:56 commits, 41 pushes, 1 branch in 3 years 9 months
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