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Lemurian Labs

Provides cost-effective AI hardware for enterprises

Graph Optimization Compiler Engineer

Systems Software EngineeringConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A Bachelor of Science degree in Computer Science or Computer Engineering, or equivalent practical experience.
  • At least 4 years of experience working with compilers, focused on intermediate representation design or optimization passes.
  • Deep knowledge of graph-level compiler optimization techniques, including fusion, tiling, and layout transformations.
  • At least 4 years of experience with C/C++.
  • Strong written and verbal communication skills and the ability to write clear, concise technical documentation.

Responsibilities

  • Design, develop, and maintain the graph optimization layer of the heterogeneous AI compiler.
  • Implement and extend graph-level transformation passes, including operator fusion, layout propagation, dead code elimination, constant folding, and algebraic simplification.
  • Define and evolve the intermediate representation to support new optimization opportunities as machine learning model architectures advance.
  • Analyze performance data to identify optimization gaps and drive measurable improvements in throughput and latency.
  • Collaborate with front-end and code-generation teams to ensure clean intermediate-representation interfaces and well-structured optimization pipelines.
  • Propose and prototype new optimization strategies in response to advances in model design and hardware capabilities.
  • Contribute to testing and validation infrastructure to ensure optimization correctness across model types and hardware targets.

Desired Qualifications

  • A Master's or PhD in Computer Science or Computer Engineering, or equivalent.
  • Experience with polyhedral models or affine analysis for loop and tensor optimization.
  • Familiarity with hardware memory hierarchies and how layout decisions affect performance on GPUs or accelerators.
  • Experience with MLIR, XLA, or similar graph-level intermediate-representation frameworks.
  • Experience with machine learning framework internals, including PyTorch eager/compile mode, JAX/XLA, or TensorRT.
  • Strong understanding of machine learning model architectures and their computational patterns, including attention, convolution, and normalization.
  • Knowledge of quantization, sparsity, or other model-level optimization techniques.
  • Contributions to open-source compiler or machine learning infrastructure projects.

About the Company

Lemurian Labs

Provides cost-effective AI hardware for enterprises

Lemurian Labs designs and sells affordable, energy-efficient AI computers for businesses to develop and deploy AI. These machines are built from first principles to deliver around 20x higher AI performance per dollar, and customers purchase them with optional long-term maintenance and upgrades. The company differentiates itself by combining high performance with low cost and low energy use, making advanced AI accessible to more organizations. Its goal is to help businesses scale AI quickly and sustainably by providing practical, affordable hardware.

Company size
11-50
Company stage
Series A
Total funding
$37.1M
Headquarters
Toronto, Canada
Founded
2018

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