Startups · AI

Compiler Engineer – MLIR / PyTorch Infrastructure

Mythic · Palo Alto, CA · Remote

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About Mythic

Backed by NEA and Lux.

About the role

Join us in advancing the MLIR ecosystem at Mythic. You’ll help extend our existing high-level dialects and design a new hardware-aware low-level dialect, building conversion paths that bridge to our current IRs. Working closely with hardware engineers and ML developers, your work will expand interoperability with PyTorch and other frameworks, laying the groundwork for long-term innovation.

What they're looking for

  • Experience architecting complete MLIR flows: from frontend dialects down to hardware-aware dialects, including conversion to and from existing IRs
  • Familiarity with PyTorch compiler technologies, especially Torch-MLIR and integration paths with PyTorch 2.0 (TorchDynamo, TorchInductor)
  • Knowledge of dataflow architectures, scheduling, and memory orchestration
  • Background in heterogeneous or specialized accelerators (e.g., analog compute, NPUs, GPUs, DSPs)
More about this role

About us

Mythic is building the future of AI computing with breakthrough analog technology that delivers 100× the performance of traditional digital systems at the same power and cost. This unlocks bigger, more capable models and faster, more responsive applications—whether in edge devices like drones, robotics, and sensors, or in cloud and data center environments. Our technology powers everything from large language models and CNNs to advanced signal processing, and is engineered to operate from –40 °C to +125 °C, making it ideal for industrial, automotive, aerospace, and defense.

We’ve raised over $100M from world-class investors including Softbank, Threshold Ventures, Lux Capital, and DCVC, and secured multi-million-dollar customer contracts across multiple markets.

About the role

Join us in advancing the MLIR ecosystem at Mythic. You’ll help extend our existing high-level dialects and design a new hardware-aware low-level dialect, building conversion paths that bridge to our current IRs. Working closely with hardware engineers and ML developers, your work will expand interoperability with PyTorch and other frameworks, laying the groundwork for long-term innovation. The...

Read the full posting on Mythic's site ↗

Compiler

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