Compiler Frontend Engineer

Normal Computing

. Extend the compiler frontend and mid-level support for new LLM architectures .

Posted 10/22/2026full-timeMountain View • California • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in extending compiler frontends and mid-level support for LLM architectures, with a strong focus on maintaining test coverage and collaborating with engineers to ensure model accuracy and performance. Proficient in Python and familiar with C++ or Rust, with hands-on experience in ML compiler development and modern LLM architectures.

Highest-signal resume keywords

ML Compiler ExperienceDeep Familiarity With PyTorch InternalsModern LLM Architectures KnowledgeFluency In PythonExperience With IREE, XLA, Or TVM

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Compiler Pass DevelopmentAttention MechanismsMoE RoutingQuantization SchemesCompiler Infrastructure DesignModel PartitioningHardware-Software Co-DesignIn-Memory Hardware Targets

Tools & Technologies

PyTorchTorchDynamoFXTorch.exportJAXONNX

Industry Keywords

LLM ArchitecturesTest CoverageSimulatorsFPGA PrototypesOpen-Source Contributions

Tech Stack

Tools & technologies

PythonPyTorchRustC++

About the role

Key responsibilities & impact

Extend the compiler frontend and mid-level support for new LLM architectures
Bring up attention variants, MoE routing schemes, and other architectures in the compiler
Extend IR, operations, and lowering passes to faithfully represent new architectural primitives
Maintain test coverage as the compiler evolves
Represent quantization schemes and numeric formats while preserving model accuracy
Track the LLM architecture landscape and recommend future bring-up priorities
Hand lowered programs to backend compiler engineers mapping them onto the hardware
Collaborate with the LLM serving engineer to move models from compiler support to serving
Validate compiler bring-up against simulators and FPGA prototypes before silicon availability

Requirements

What you’ll need

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
Comfort designing compiler infrastructure in a young codebase and extending an established one
Comfort building software for evolving hardware, from simulation through bring-up
Fluency in Python
Familiarity with C++ or Rust
Experience with IREE, XLA, or TVM is a bonus
Familiarity with JAX or ONNX is a bonus
Experience partitioning models across devices using tensor, pipeline, or expert parallelism is a bonus
Experience with hardware-software co-design is a bonus
Experience with non-standard or in-memory hardware targets is a bonus
Contributions to open-source compiler or ML infrastructure projects are a bonus

Benefits

Comp & perks

Research-adjacent role with opportunity to publish on behalf of Normal
Work on pre-silicon hardware using simulators and FPGA prototypes
Inclusive work environment and Equal Employment Opportunity commitment
Reasonable accommodations for individuals with disabilities