Mythic

Power-efficient edge AI processors for inference

Compiler Engineer - Machine Learning Compiler

Systems Software EngineeringConfirmed live in the last 24 hours

Full-timeNo salary listedRemote

About the Job

Requirements

At least 3 years of experience building compilers or high-performance systems software, especially involving complex resource management or optimization.
Expertise in modern C++ (C++14, C++17, or C++20) and strong Python skills.
Experience with compiler intermediate representations (SSA-based or graph-based), transformations, and code generation.
Exposure to specialized accelerators such as GPUs, NPUs, FPGAs, or custom ASICs, or to parallel architectures.

Responsibilities

Contribute across the full compiler stack, including operator lowering, graph and intermediate-representation transformations, optimization passes, and backend code generation.
Optimize for dataflow architectures by developing pipelined schedules, memory orchestration, and resource-constrained execution strategies.
Collaborate with hardware architects to influence architectural features and ensure the compiler and hardware evolve together.
Develop compilation strategies that unify 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.

Desired Qualifications

Experience with machine learning compiler stacks such as ONNX, MLIR, TVM, XLA, IREE, or PyTorch; contributions to MLIR or LLVM projects are a plus.
Experience with optimization methods such as linear programming, mixed-integer programming, constraint programming, SAT, or SMT using solvers such as Gurobi or OR-Tools for scheduling and resource allocation.
Experience compiling for specialized accelerators such as GPUs, NPUs, FPGAs, or custom ASICs on deep neural network workloads; GPU or DSP experience is valuable when combined with compiler backend work beyond kernel tuning.
Familiarity with heterogeneous compilation, especially mixing custom accelerators with CPUs, GPUs, or NPUs, and exposure to analog or in-memory compute.
Experience collaborating in compiler-hardware co-design, including architecture and instruction set architecture, to improve compiler usability and hardware efficiency.

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.

Here's what you will do

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

Here's the background we hope you will have

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

The following would be nice to have, but is not required

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

What we offer

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

At Mythic, we foster a collaborative and respectful environment where people can do their best work. We hire smart, capable individuals, provide the tools and support they need, and trust them to deliver. Our team brings a wide range of experiences and perspectives, which we see as a strength in solving hard problems together. We value professionalism, creativity, and integrity, and strive to make Mythic a place where every employee feels they belong and can contribute meaningfully.

About the Company

Mythic

Power-efficient edge AI processors for inference

Mythic designs power-efficient AI hardware for edge deployments. Its main products are the M1076 Analog Matrix Processor, a single-chip accelerator that can run at up to 25 TOPS, and the MP10304 Quad AMP PCIe card, which adds more performance for AI inference on edge devices and servers. The hardware uses analog matrix processing to perform AI computations with low energy usage, enabling high-performance inference in real-world environments without relying on cloud servers. Mythic targets customers that need strong AI performance with tight power budgets, such as tech companies and other businesses with heavy data-processing needs. Compared with typical AI accelerators, Mythic emphasizes analog computation and edge efficiency, offering a compact single-chip solution plus an expansion PCIe card to scale performance. The company's goal is to make high-performance AI inference practical at the edge by delivering power-efficient processors and modules for edge devices and servers.

Company size: 51-200
Company stage: Late Stage VC
Total funding: $290.4M
Headquarters: Austin, TX
Founded: 2012

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