Compiler Engineer

Role overview Develop compiler technology that makes AI model inference faster and more efficient across cloud and edge environments. You’ll optimize computation graphs, lower neural network representations, and build hardware-specific execution paths for GPUs, TPUs, and newer accelerator types.

Responsibilities - Create optimizing compiler components and graph transformation passes for large language model inference. - Use compiler intermediate representations to generate efficient machine code and kernel calls. - Improve memory management and execution techniques, including KV caching, speculative decoding, and paged attention. - Benchmark and profile performance, with attention to throughput and cost per generated token.

Requirements - Strong C++ and/or Rust skills and a deep understanding of compiler architecture, including frontends, intermediate representations, optimization passes, and backends. - Familiarity with MLIR, LLVM, or machine learning graph compilation tools such as TVM, XLA, TensorRT, or TorchDynamo. - Understanding of GPU architecture, including tensor cores, shared memory, compute capabilities, and warp scheduling. - Careful approach to performance measurement, micro-benchmarks, and regression testing.

Nice to have - Experience writing CUDA or Metal kernels for attention or fused operations. - Contributions to open-source compiler or runtime projects.

Benefits and work setup - Remote-first work with a globally distributed team. - High autonomy and ownership, with opportunities to publish work that developers can inspect and build on.