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The Machine Learning Frameworks team exists for two reasons: making the research iteration loop as fast and frictionless as possible, and making production run as fast as the hardware allows. Both matter, and figuring out how to do both at once is most of what makes the work fun.
Concretely, we build optimisers, code generators, runtime libraries, and the orchestration layer that runs computation across heterogeneous hardware. The stack spans C++, Rust, Python, MLIR, and CUDA. You don't need to know all of these things but should be excited about working in this space.
The work is broad. Some of…
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