Top Engineering Jobs in London

Build and operate Kubernetes-based infrastructure and tooling to support development, testing, deployment and scaling of Graphcores ML software. Manage cloud infrastructure, CI/CD practices, and collaborate with software teams to improve reliability and observability of HPC AI platforms.

Design, deploy, and maintain tools and services for build, CI/CD, packaging, and releases. Manage cloud and Kubernetes infrastructure, use IaC, reduce toil, and support junior engineers for reliable ML software delivery.

Develop and maintain internal build, test, and integration tooling for the ML software stack. Build release processes, assist dependency management, guide developers on build best practices, collaborate with QA and engineers to resolve integration issues, and contribute fixes to the ML software stack.

Develop, manage, and sustain tools and services for software build, test, deployment, and release. Build and maintain API integrations and automation workflows, support Linux-based environments, and improve reliability while reducing operational toil. Mentor junior and graduate engineers and collaborate across engineering and security teams.

The Senior Systems Engineer focuses on analyzing performance data from systems, ensuring stability for production, and using engineering judgment for decision-making in a high-performance computing context.

Develop and deploy cloud services, optimize AI systems, and work on infrastructure automation while collaborating with various teams.

The engineer will evaluate large-scale Linux systems, design workloads, build execution systems, interpret results, and ensure reliability for production readiness.

As a Staff Software Engineer (ML QA), you'll design and maintain testing infrastructure for the ML software stack, focusing on automation, software quality, and mentoring junior engineers in a collaborative environment.