Ray Yang is a Senior Staff Software Engineer with 13 years of experience building OS- and kernel-level systems for security, malware analysis, and high-performance computing across consumer and enterprise markets. Based in Milpitas, he has led low-level Windows guest system development and custom VM work at Mandiant, and previously drove kernel components and reverse-engineering efforts at Symantec and endpoint protection at ThreatMetrix. He blends deep systems programming with ML research experience—contributing TPU-serving and model-export improvements to Tensor2Tensor—and currently engages in LLM, NLP and ML research at Google DeepMind. Known for tackling hard interactions between software and hardware, he focuses on reliability and performance in production environments while maintaining a strong defensive-security perspective.
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Role in this project:
ML Engineer
Contributions:9 commits in 6 months
Contributions summary:Ray primarily focused on improving the Tensor2Tensor library's functionality, especially around model serving and TPU integration. They implemented and refined serving input functions to handle features correctly, particularly when using TPUs. Additionally, they introduced features to enhance model exporting and performance optimization, including the ability to mark weights as constants and configuring batch sizes for TPU inference. These changes aimed to streamline deployment and improve efficiency in the context of deep learning models.
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Ray Yang - Senior Staff Software Engineer at Mandiant