> Markdown version of [/jobs/ext/2715131-compiler-engineer-machine-learning-compiler](https://www.wearedevelopers.com/jobs/ext/2715131-compiler-engineer-machine-learning-compiler). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Compiler Engineer - Machine Learning Compiler - **Company:** Mythic Inc. - **Location:** Palo Alto, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, C++ (Programming Language), Code Generation, Software Debugging, Microprocessors, Data Flow Control, Field-Programmable Gate Array (FPGA), Python (Programming Language), Machine Learning, Software Engineering, Graphics Processing Unit (GPU), Application Specific Integrated Circuits, Pytorch, Deep Learning, Parallel Computation, Backend, ONNX (Open Neural Network Exchange) Format, C++14 - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/compiler-engineer-machine-learning-compiler-mythic-8295174 ## About the Role * 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 ## Description 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 ## Related Videos - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Building a Compiler with C#](https://www.wearedevelopers.com/videos/116-building-a-compiler-with-c) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Unleashing the Full Potential of the Arm Architecture – Write Once, Deploy Anywhere](https://www.wearedevelopers.com/videos/940-unleashing-the-full-potential-of-the-arm-architecture-write-once-deploy-anywhere) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 129 - Now that's what I call private data!](https://www.wearedevelopers.com/magazine/468-dev-digest-129-now-that-s-what-i-call-private-data) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)