Platform Engineer

Platform Engineer – HPC, AI and ML Up to £80,000 plus benefits Onsite – Kensington, London Company and Role This is an opportunity to join a global technology and AI solutions provider delivering some of the most advanced computing platforms in the world. You will play a leading role in the design, build and long-term support of a next generation AI and Machine Learning platform, built on cutting-edge High Performance Computing (HPC) infrastructure for one of the UK’s most prestigious research environments. As a Platform Engineer – HPC, AI and ML, you will be responsible for building and optimising a high-performance platform purpose-built for AI, ML, LLM and Generative AI workloads. You will lead on architecture, deployment and performance tuning using technologies such as Kubernetes, NVIDIA Run:AI, Ubuntu, Weka NeuralMesh and HGX B200 GPU nodes. Once live, you will take ownership of the platform’s operation and evolution, ensuring it delivers consistent world-class performance for advanced research workloads. It is a rare opportunity to build a complex HPC environment from the ground up and then own it, ensuring it continues to power the next generation of AI-driven innovation. Why This Role Stands Out • Be part of one of the UK’s most advanced AI and HPC platform projects • Build and then support a world-class infrastructure enabling AI, ML, LLM and Generative AI research • Collaborate with global technology leaders including NVIDIA, HPE, Canonical and Weka • Onsite role in Kensington, London within a pioneering research and innovation environment • Salary up to £80,000 with excellent opportunities for growth in HPC and AI infrastructure engineering What You’ll Be Doing • Designing, deploying and configuring a complete AI and ML operations platform within a large-scale HPC environment • Installing and optimising Ubuntu (Canonical) across GPU and non-GPU compute nodes • Implementing and managing Kubernetes for container orchestration and performance at scale • Installing and configuring NVIDIA GPU Operator, Network Operator and Run:AI orchestration platform • Integrating Run:AI with Kubernetes clusters to deliver scalable GPU utilisation • Supporting deployment of HGX B200 GPU nodes (96 NVIDIA B200 GPUs) and associated infrastructure • Managing Weka NeuralMesh distributed AI storage for high-speed data access and resilience • Implementing CI/CD and MLOps pipelines using Argo Workflows, Jenkins and GitHub • Monitoring platform performance using Zabbix, Prometheus and Grafana • Integrating SAN and Infiniband networking to achieve high throughput and reliability • Creating detailed documentation and performing knowledge transfer to operations teams • Providing ongoing platform support, patching, troubleshooting and continuous improvement What You’ll Bring • Proven experience designing, deploying and supporting HPC or large-scale compute environments for AI and ML workloads • Strong understanding of Ubuntu server administration, networking and performance tuning • Hands-on experience with Kubernetes and GPU-enabled workloads • Practical knowledge of NVIDIA GPU technologies, particularly GPU Operator and Run:AI • Familiarity with distributed storage and AI data systems such as Weka NeuralMesh • Experience with CI/CD and MLOps pipelines using Argo, Jenkins or GitHub • Knowledge of HPC networking including SAN and Infiniband integration • Strong troubleshooting and documentation skills with a collaborative mindset Desirable Experience • Certifications in Kubernetes, NVIDIA or HPC infrastructure technologies • Experience in research, academic or scientific computing environments • Understanding of AI and ML workflows, neural network training and large language models • Familiarity with HPE, NVIDIA, Aarna and Digital Realty platforms If you are passionate about building and operating large-scale computing environments and want to play a key role in delivering one of the UK’s most advanced HPC and AI platforms, this is your opportunity to shape the future of research and machine learning infrastructure.