We're building cutting-edge AI accelerator solutions, spanning hardware and software, and we're looking for a Software Engineer to join our Developer Experience team to help us scale fast, build smart, improve our internal developer experience, and help shape the developer experience others will have with our accelerator.

We have multiple teams who produce different software and hardware components including;

• Machine Learning models in Python.
• Compilers to create representations of LLMs to operate on our hardware.
• Linux kernel drivers, and low level system software, written in C, C++23, and Rust.
• RTL written in SystemVerilog.
• Create hardware verifiers, simulators, and designs using Cocotb, Verilator, and Icarus Verilog.
• Run hardware simulations on large core count servers and VMs.

Our workflows are built around Bazel in a monorepo with GitHub Actions for CI/CD, and our teams produce software that runs on Apple Silicon Macs, both ARM and x86-64 systems running Linux, RISC-V, and our own hardware.

What You’ll Be Doing

• Improving our developers day-to-day workflow.
• Creating the experience that will define how our customers will interact with our accelerators.
• Finding solutions to ensure our Bazel builds, monorepo, and CI configuration can scale as we grow our company.
• Create, debug, and optimise our Bazel build rules.
• Contribute to upstream Bazel rules that we use.
• Manage and optimise our CI compute cluster, and help other teams with our other compute clusters.
• Extend support for new languages and technologies.
• Work Hybrid on-site, in one of our UK offices (Bristol, or possibly London), at least three days per week.

What We Hope You Will Bring

• 5 years experience in Software Engineering or Infrastructure Engineering.
• 3 years of experience with build tools.
• Experience building and maintaining advanced CI/CD pipelines for large-scale products.
• Proficiency with Bazel.
• 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).