What this interview will probe
Designs and develops the Tungsten language compiler that maps deep-learning workloads onto the Cerebras Wafer-Scale Engine, owning IR design, optimization passes, and code generation for a massively parallel custom-silicon target. Collaborates with hardware and kernel teams to extract performance from the WSE's on-wafer memory and fabric. A technical interview would probe compiler internals (dataflow analysis, loop/tiling transformations, IR lowering through MLIR/LLVM) and reasoning about scheduling computation across a non-von-Neumann architecture.
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