We're partnering a startup who are building software that helps bring cutting-edge AI research into production environments. This means solving challenging problems in distributed computing, deployment automation, infrastructure orchestration, and performance optimisation across modern hardware platforms.

What You'll Work On Build and improve platform services that support large-scale AI and compute workloads Develop software that orchestrates workloads across GPUs, multicore CPUs, and distributed environments Design and maintain deployment pipelines that help move new capabilities from development into production Improve the reliability, observability, and scalability of platform infrastructure Collaborate with researchers and engineers to turn experimental systems into robust production services Investigate performance bottlenecks and optimise systems for efficiency Contribute to engineering best practices, testing, automation, and code quality initiatives

What We're Looking For Professional experience developing software in Python on Linux-based systems Experience building or operating backend services, platform infrastructure, or distributed systems Familiarity with container technologies, CI/CD workflows, and Kubernetes Strong problem-solving skills and an interest in understanding how complex systems fit together Ability to work collaboratively across technical disciplines Interest in modern AI, machine learning, or high-performance computing technologies

Why Join? Work on technically challenging problems at the intersection of AI, distributed systems, and cloud infrastructure Gain exposure to modern high-performance computing environments and emerging AI technologies Collaborate with experienced engineers and researchers in a highly technical environment Flexible working arrangements and opportunities for professional growth Access to cutting-edge hardware and software platforms