Joel Wee is a software engineer with 8 years’ experience building and operating large-scale distributed systems, currently working on infrastructure to scale large models at DeepMind. He has production experience managing thousands of Kafka clusters at AWS, improving automated self-healing and zero-downtime updates to raise operational success from 99% to 99.9%. A Cambridge-trained mathematician, Joel combines strong systems engineering with DevOps expertise—evidenced by contributions to the LLVM project’s MLIR Bazel build and dependency fixes. His background spans backend services, cloud operations, and full-stack projects from Python/React products to infrastructure tooling, and he brings practical, reliability-focused thinking informed by prior leadership roles in the Singapore Armed Forces.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Arts and Masters of Mathematics, Mathematics, First Class Honours, Bachelor of Arts and Masters of Mathematics, Mathematics, First Class Honours at University of Cambridge
High School, High School at St. Andrew's Junior College, Singapore
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
Role in this project:
Backend Developer & DevOps Engineer
Contributions:6 reviews, 8 PRs, 19 pushes in 1 year 5 months
Contributions summary:Joel primarily contributed to build system configuration and dependency management within the MLIR project, specifically targeting Bazel. Their commits focused on resolving build failures, updating dependencies, and ensuring compatibility with the build environment. These changes involved modifications to the Bazel build files, and also included fixes for clang and libc build related issues.
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