Senior ML Infrastructure Engineer

About this role

At the Ellison Institute of Technology (EIT), we’re on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, policy makers, and entrepreneurs to tackle humanity’s greatest challenges in four transformative areas: Health, Medical Science & Generative Biology Food Security & Sustainable Agriculture Climate Change & Managing CO₂ Artificial Intelligence & Robotics This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you’ll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas for lab to society. Explore more at www.eit.org Requirements Our MLOps team Join our MLOps team to build the cloud and compute foundation that enables scientific breakthroughs. Deliver reliable, secure platforms and self-service guardrails that accelerate experimentation and turn ideas into results—faster, at scale, and with confidence. Day-to-day, you might: Build, operate, and continuously optimise our high-performance GPU training and inference clusters, focusing on robust, high-availability scheduling, isolation, and automated lifecycle management. Drive systems design and implementation for high-throughput data paths, optimising I/O, caching, and data locality across compute and storage (including our current Lustre implementation). Proactively benchmark, profile, and resolve performance bottlenecks across the compute, network, and orchestration layers to maximise efficiency for distributed training and inference. Establish comprehensive observability, resilience, and automated security controls to ensure compliance and robust operation of sensitive research environments. Partner with Research, Data, and Applied teams to forecast capacity and cost for GPU and storage needs, setting quotas and streamlining ML experimentation pipelines. What makes you a great fit: Proven experience leading the design, build, and operation of high-performance ML compute clusters at scale A proactive, autonomous approach to systems design and the proven ability and desire to ideate, co-create and implement optimal solutions Exposure to migrating or transforming ML infrastructure from traditional schedulers to modern, containerised systems Expertise with high-throughput storage systems for ML/HPC workloads Expert-level understanding of GPU architecture, high-speed networking for distributed training, and performance profiling to resolve bottlenecks A solid grasp of IaC and CI/CD practices (e.g., Terraform, Argo CD) Benefits We offer the following salary and benefits: Enhanced holiday pay Pension Life Assurance Income Protection Private Medical Insurance Hospital Cash Plan Therapy Services Perk Box Electric Car Scheme -- Why work for EIT: At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!