Mythic Ai.Com7mo ago

Compiler Engineer - Machine Learning Compiler

United States·Palo AltoRemoteFull-timemid

Data ScienceSoftware EngineeringCompiler Engineer

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Quick Summary

Overview

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.

Technical Tools

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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 building the next generation of AI compilers. You’ll play a key role in developing the compiler for our novel AI accelerator, working side-by-side with hardware engineers and ML researchers. Your work will shape how deep learning workloads run on cutting-edge dataflow hardware—defining the instruction set, execution model, and developer experience. The result: a compiler that delivers breakthrough performance while remaining seamless and intuitive for ML developers.

Contribute across the full compiler stack, including operator lowering, graph/IR transformations, optimization passes, and backend code generation

Optimize for dataflow architectures, developing pipelined schedules, memory orchestration, and resource-constrained execution strategies

Collaborate with hardware architects to influence architectural features, ensuring the compiler and hardware evolve together

Develop compilation strategies that unify our analog compute with digital subsystems

Build and maintain a compiler that produces high-performance binaries with strong debugging support, clear error messages, and predictable performance models

3+ years of experience building compilers or high-performance systems software, especially those involving complex resource management or optimization.

Expert in modern C++ (C++14/17/20) and strong Python.

Experience with compiler IRs (SSA-based or graph-based), transformations, and code generation

Exposure to specialized accelerators (GPU, NPU, FPGA, or custom ASIC) or parallel architectures

Experience with machine learning compiler stacks (e.g., ONNX, MLIR, TVM, XLA, IREE, PyTorch), with contributions to MLIR or LLVM projects a plus

Experience with optimization methods (LP/MIP, CP, SAT/SMT) using solvers like Gurobi or OR-Tools for scheduling and resource allocation

Experience compiling for specialized accelerators (GPU, NPU, FPGA, or custom ASIC) on DNN workloads; GPU/DSP experience is valuable if combined with compiler backend work beyond kernel tuning

Familiarity with heterogeneous compilation, especially mixing custom accelerators with CPUs/GPUs/NPUs, and exposure to analog or in-memory compute is a plus

Experience collaborating in compiler–hardware co-design (architecture + ISA) for better compiler usability and hardware efficiency

The opportunity to shape how deep learning and LLM workloads are compiled on novel hardware.

A role that spans software and hardware co-design, shaping both the compiler and the accelerator architecture

A collaborative, innovative team that values engineering rigor, continuous integration, and user-focused design. We foster an environment of shared learning and technical excellence

Competitive compensation, equity, and benefits package