Front End Compiler

Lemurian LabsToronto, ON

About The Position

We're looking for a Front End Compiler Engineer to own the ingestion layer of our high-performance, portable AI compiler. This is where the journey begins — you'll build the systems that parse, validate, and lower representations from frameworks like PyTorch, StableHLO, ONNX, and MLIR dialects into our internal compiler IR, setting the stage for everything that follows. If you're drawn to the elegance of well-designed language frontends, care deeply about correctness and coverage, and want your work to directly enable next-generation AI models to run anywhere — this is the role for you.

Requirements

  • BS degree in Computer Science or equivalent practical experience
  • 2+ years of experienceWorking with ML optimization tools/libraries
  • Experience working with or ingesting from ML frameworks such as PyTorch, TensorFlow/JAX, or ONNX
  • 2+ years of experience with C/C++ and 2+ years working with Python
  • Strong written and verbal communication skills; ability to write clear and concise technical documentation
  • Knowledge of quantization, sparsity, or other model-level optimization techniques

Nice To Haves

  • Master's or PhD in Computer Science or equivalent
  • Experience with StableHLO, XLA, or other ML-specific IRs
  • Knowledge of operator semantics across ML frameworks and the challenges of cross-framework compatibility
  • Familiarity with Python bindings and tooling for compiler front ends
  • Experience with testing infrastructure for compiler correctness — fuzzing, differential testing, or model-level validation
  • Contributions to open-source compiler or ML framework projects
  • Familiarity with MLIR, including defining and working with custom dialects

Responsibilities

  • Design, develop, and maintain the front end of our heterogeneous AI compiler, including parsing, validation, and IR lowering stages
  • Build and extend ingestion pipelines for ML frameworks and representations including PyTorch, StableHLO, ONNX, and MLIR-based dialects
  • Define and evolve the interface between external model representations and our internal compiler IR
  • Ensure correctness and completeness of operator coverage across supported frameworks and hardware targets
  • Collaborate with graph optimization and code generation teams to ensure clean, well-structured IR that enables downstream transformations
  • Use performance and correctness data to identify gaps in coverage and drive improvements
  • Contribute to documentation and tooling that helps ML engineers understand and debug the ingestion process

Benefits

  • Competitive compensation including equity, medical/dental/vision, retirement savings, and wellness benefits
  • Additional benefits include equity, company bonus opportunities, medical, dental, and vision coverage, a retirement savings plan, and supplemental wellness benefits.
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