Join a global, technology-driven organisation as a Platform Engineer, designing and building distributed systems that power large-scale computational research infrastructure.
The role sits at the intersection of distributed systems, platform engineering, and high-performance computing (HPC) , working on foundational services used by highly technical research and engineering teams.
Company OverviewA global technology-led organisation operating large-scale, data-intensive and computationally demanding systems. Engineering is central to the business, with significant investment in distributed computing, research infrastructure, and high-performance platforms.
TeamYou will join a specialist platform engineering team responsible for building the infrastructure and services underpinning large-scale computational research.
Key Responsibilities- Design, build, and operate distributed services managing compute workloads and data access across large-scale infrastructure
- Develop platform APIs and tooling to improve researcher and developer productivity
- Improve the reliability, scalability, and performance of compute-intensive workflows
- Build solutions across workload orchestration, resource management, observability, and security
- Translate complex research and infrastructure requirements into scalable platform capabilities
- Take end-to-end ownership from system design and implementation through to production operation
- 8-12+ years building and operating large-scale distributed systems in production
- Strong programming skills in C++, Java, Rust, Go , or similar systems languages
- Strong understanding of distributed systems, concurrency, performance, reliability, and fault tolerance
- Experience designing platforms, services, or infrastructure used by other engineers
- Degree in Computer Science or a related technical discipline, or equivalent practical experience
- Internal developer platforms, cloud infrastructure, orchestration systems, or HPC
- GPU-accelerated computing and/or ML infrastructure
- PyTorch, TensorFlow, or similar frameworks
- Experience supporting researchers, data scientists, or highly technical engineering users
- Large-scale, data-intensive or performance-sensitive environments
- Solve complex distributed systems and infrastructure problems at significant scale
- Build platforms that directly accelerate computational research
- Work on challenging problems across HPC, distributed computing, orchestration, and platform engineering
- High degree of technical ownership and autonomy
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