Senior Build & ML Infrastructure Engineer

Graphcore; West of England; On-site; GBP 60,000 - 80,000; Full time

Benefits offered by this job

Flexible working

Generous annual leave

Private medical insurance

Dental plan

Matched pension up to 5%

Life assurance

Income protection

Parental leave

Job summary

Graphcore is hiring for a Build Engineer within the Software Operations team in Bristol. You will scale and manage our infrastructure, building essential tooling for the ML software stack and supporting release processes.

You will work closely with QA and developers to ensure the ML stack is reproducible in secure environments, using Python/C++ and Linux-based workflows. The role emphasizes build practices, containerisation, and SDLC compliance.

Qualifications

• Experience developing and maintaining ML software stacks in Linux.
• Strong knowledge of Python and C++ in a build/automation context.
• Familiarity with CI/CD, containerization and distribution of software.
• Ability to communicate with engineers across teams and document processes.
• Hands-on experience with build systems and dependency management.

Responsibilities

• Develop internal tooling for building, testing and integrating the ML software stack.
• Create tools and processes for Software Releases and deployment.
• Advise developers on build best practices and dependency management.
• Collaborate with QA and development teams to ensure stack integrity.
• Contribute fixes to the ML Software Stack and improve test coverage.

Skills

Python/C++

Build systems

Linux environments

Communication

RemoteCaching/Execution

Build tools

Testing frameworks

Integration tooling

SDLC

Containers

Software architecture

Tools

Bazel

CMake

Buildstream

PyTest

GoogleTest

Docker

Podman

Job description

Graphcore is hiring for a Build Engineer within the Software Operations team in Bristol. You will scale and manage our infrastructure, building essential tooling for the ML software stack and supporting release processes.

You will work closely with QA and developers to ensure the ML stack is reproducible in secure environments, using Python/C++ and Linux-based workflows. The role emphasizes build practices, containerisation, and SDLC compliance.