Yee Tong is a software engineer with 13 years of experience building scalable data and ML infrastructure, currently at Union.ai and co-creator of the open-source Flyte orchestration platform. He brings a rare blend of production backend, DevOps, and data engineering expertise from roles at Lyft and The Climate Corporation, where he built Hive-based analytics, experiment platforms, and resilient messaging systems. His early career in fixed-income research at BlackRock gives him strong quantitative instincts and domain fluency for designing data-driven systems. On GitHub he has contributed substantial enhancements to flyteorg/flyte and flytekit, improving SDK extensibility, auth integration, and Kubernetes/EKS deployments for real-world workloads. Based in Seattle, he focuses on practical, deployable solutions that bridge developer ergonomics with robust, scalable infrastructure.
13 years of coding experience
12 years of employment as a software developer
Bainbridge High School
BS, Electrical and Computer Engineering, 3.5, BS, Electrical and Computer Engineering, 3.5 at Cornell University
Extensible Python SDK for developing Flyte tasks and workflows. Simple to get started and learn and highly extensible.
Role in this project:
Back-end Developer
Contributions:182 releases, 1804 reviews, 1817 commits in 4 years 5 months
Contributions summary:Yee's commits focus on enhancing the FlyteKit Python SDK, specifically concerning core functionality, including handling tasks such as hive queries, and adding features like defining and calling sub-workflows. They've worked to refactor Auth configurations to improve the integration of gRPC and HTTP endpoints. In addition, the user has contributed to the build process by including an option to customize the image name.
Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
Role in this project:
DevOps Engineer
Contributions:3 releases, 484 reviews, 345 commits in 3 years 2 months
Contributions summary:Yee primarily contributed to the deployment and configuration aspects of the Flyte platform. Their work included updating sandbox deployments by modifying scripts and configurations for various components, as well as adding and configuring EKS deployments. They also added documentation for setup and configuration and focused on external eventing. Their contributions were focused on infrastructure, deployment, and integrating external services.
pythondatamission-criticalgrpcproduction-grade
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