Yao Weng is a New York–based Software Engineer with 8 years of experience, currently a Senior Software Engineer on Bloomberg's Data Science Platform team. He holds a Ph.D. in Physics from Cornell, bringing research rigor and quantitative thinking to production engineering. At Bloomberg he has worked across real-time volatility and data science platform efforts, translating complex financial and ML requirements into reliable services. An active open-source contributor in MLOps, he has helped productionize ML inference on Kubernetes through contributions to the kserve/kserve project—adding multi-model serving configuration, load/unload endpoints, storage test fixes, and improved Docker and testing workflows. He blends deep analytical training with pragmatic deployment skills to move models from prototype to scale.
8 years of coding experience
7 years of employment as a software developer
B.S, Physics, B.S, Physics at Central China Normal University
Standardized Serverless ML Inference Platform on Kubernetes
Role in this project:
MLOps Engineer
Contributions:7 reviews, 5 commits, 16 PRs in 8 months
Contributions summary:Yao primarily contributed to the configuration and deployment of machine learning models within the kserve/kserve platform. Their work included fixing storage tests related to minio, adding and modifying configuration maps for multi-model serving, and integrating load/unload endpoints for model management. They also updated testing procedures and docker configurations.
Envoy AI Gateway is an open source project for using Envoy Gateway to handle request traffic from application clients to Generative AI services.
Contributions:44 pushes, 6 branches in 3 months
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