Compiler Engineer (AI)

Location: Mountain View, United States; hybrid work

Company

hirify.global is an applied AI company developing foundational hardware and software for the semiconductor industry, AI infrastructure, and systems applications. Its hardware executes memory-bound large-model inference inside memory, with compiler software for programming the platform.

What you will do

• Bring up frontend and mid-level compiler support for new LLM architectures, including attention variants and MoE routing schemes.
• Extend the IR, operations, and lowering passes to represent new architectural primitives faithfully and maintain test coverage.
• Represent model quantization schemes and numeric formats while preserving model accuracy during lowering.
• Track the LLM architecture landscape and recommend which architectures to bring up next.
• Validate compiler bring-up through simulators and FPGA prototypes for pre-silicon hardware.
• Hand lowered programs to backend compiler engineers and collaborate with LLM serving engineering to move models from compiler support to serving.

Requirements

• Hands-on ML compiler experience, including writing and shipping compiler passes.
• Deep familiarity with PyTorch internals, ideally including TorchDynamo, FX, and torch.export.
• Working knowledge of modern LLM architectures, including attention mechanisms, MoE routing, and quantization schemes.
• Ability to develop compiler infrastructure in both young codebases and established codebases.
• Experience building software for evolving hardware, from simulation through bring-up.
• Fluency in Python and familiarity with C++ or Rust.
• Patience for taking new architectures from initial execution to correct and optimized execution.

Nice to have

• Experience with ML compilers such as IREE, XLA, or TVM.
• Familiarity with ML frameworks and graph formats such as JAX or ONNX.
• Experience partitioning models across devices using tensor, pipeline, or expert parallelism.
• Experience with hardware-software co-design.
• Experience with non-standard or in-memory hardware targets.
• Contributions to open-source compiler or ML infrastructure projects.

Culture & Benefits

• Hybrid work based in Mountain View.
• Research-adjacent work with an expectation to follow relevant literature and publish on behalf of Normal.
• Collaboration across teams and offices in New York City, Silicon Valley, London, Copenhagen, and Seoul.
• Inclusive equal-opportunity workplace with reasonable disability accommodations.