Driving Infrastructure for the Future of AI Acceleration.
We're building cutting-edge AI accelerator solutions, spanning hardware and software, and we're looking for a Software Engineer -- Build System to help us scale fast, build smart, and stay ahead of the curve.
We use a Monorepo to build the entire stack, from the RTL written in SystemVerilog to the state of the art machine learning models in Python and everything in between including C, C++23, Rust and Ruby. We compile our tools for both macOS (arm64) and Linux (x86, arm64) and we also create RISC-V binaries that will run on our bespoke hardware. Cocotb, Verilator, and Icarus Verilog are used to build and simulate the RTL. SystemC, Docker, QEMU and Linux buildroot are used for simulation. Our compiler is built using MLIR. Everything mentioned here is configured, built and tested using Bazel and we run a shared CI between the whole company.
What You'll Be Doing
* Take ownership of the monorepo itself, making sure it scales are we grow our company,
* Add new features such as remote execution, shared caches, hermetic system dependencies.
* Scale the CI resources from a single machine per architecture to a managed cluster for compute resources,
* Debug and optimise build rules for existing technologies,
* Extend support for new languages and technologies,
* Contribute to upstream Bazel rules that we use,
What We Hope You Will Bring
* 5 years experience in Software Engineering or Infrastructure Engineering
* 3 years of experience with building tools or systems for developers.
* Proficiency with Bazel
* Familiarity with how C/C++, Rust, Python languages are compiled and executed,
* Experience building and maintaining advanced CI/CD pipelines for large-scale products
* Scripting and automation skills in Python
* A degree in Computer Science, Engineering, or a related field (or equivalent experience
Additional Skills That Are Nice To Have
* Experience working with machine learning pipelines or large language models
* Knowledge of GitHub Actions, and modern cloud services
* Knowledge of build systems for complex, multi-language projects
* Strong background in containerisation and orchestration technologies (Docker, Kubernetes)