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Compiler Engineer – MLIR / PyTorch Infrastructure

1 hour, 59 minutes ago
United States, Canada
Full-time
Mid Level
AI Engineer
Software Development
C++ Python PyTorch
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Mythic

Mythic

Mythic revolutionizes edge AI with power-efficient analog compute in memory technology, enabling affordable and powerful AI solutions from data centers to edge devices.

Semiconductors & Semiconductor Equipment
51-250
Founded 2012
$165M raised
View All Jobs 4

Description

  • Architect the migration of the existing compiler flow into MLIR by defining dialects, passes, and lowering strategies.
  • Build conversion paths between MLIR and Mythic’s custom low-level IR to keep both compilation flows operational during migration.
  • Define validation infrastructure within MLIR, including interpretation or execution paths for simulation and debugging.
  • Enable compilation across analog accelerators and digital subsystems through MLIR integration.
  • Leverage Torch-MLIR for PyTorch inputs when available.
  • Guide future integration with PyTorch 2.0 compiler technologies, including TorchInductor and TorchDynamo.
  • Collaborate closely with hardware engineers and ML developers on compiler and framework integration.
  • Help shape the MLIR ecosystem and long-term compiler architecture at Mythic.

Requirements

  • 3+ years of experience in compiler or high-performance systems development.
  • Proficiency in modern C++ (C++14/17/20) and Python.
  • Hands-on experience with MLIR, including dialect design, compiler passes, or lowering pipelines.
  • Strong understanding of compiler IRs and transformations.
  • Ability to reason about lowering from high-level operations to hardware-aware representations.
  • Experience architecting complete MLIR flows from frontend dialects to hardware-aware dialects, including conversion to and from existing IRs (nice to have).
  • Familiarity with PyTorch compiler technologies, especially Torch-MLIR and integration paths with PyTorch 2.0, TorchDynamo, and TorchInductor (nice to have).
  • Knowledge of dataflow architectures, scheduling, and memory orchestration (nice to have).
  • Background in heterogeneous or specialized accelerators such as analog compute, NPUs, GPUs, or DSPs (nice to have).

Benefits

  • Competitive compensation and equity.
  • Comprehensive benefits.
  • Opportunity to shape the MLIR and PyTorch integration strategy for novel AI hardware.
  • Chance to contribute upstream and influence the broader ML compiler ecosystem.
  • Collaborative team spanning hardware, runtime, and compiler design.

Interested in this position?

Apply directly on the company website

Apply Now

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