Senior ML Infrastructure Engineer

# Senior ML Infrastructure Engineer > Ellison Institute of Technology · Oxford, United Kingdom (Hybrid) · — · Posted 2026-09-08 **Workplace:** hybrid **Department:** Central Business Operations & Other ## Description **Join us at EIT:** 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 [](https://www.eit.or) **Your Role:** Join our SciComp 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. **Your Responsibilities:** - 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. ## Requirements **Essential Skills, Qualifications & Experience:** - 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:** - Competitive salary (dependent on experience) + travel allowance + bonus - Enhanced holiday. Our annual leave allowance is 25 days plus 8 bank holidays and an additional 3 days between Christmas and New Year. You will also have the opportunity to purchase an additional 5 days annual leave in January and July. - Pension - Employer contribution 7.5%, minimum employee contribution 5% - Life Assurance. - Income Protection - Private Medical Insurance as standard for you, your partner and any dependents. Including hospital Cash Plan - Employee discounts - Electric car scheme - Nursery Salary Sacrifice scheme - Cycle to Work Scheme - Family Planning - Neurodiversity support including advise and assessments - Coaching & Therapy services **Working together - what it involves:** You must have the right to work permanently in the UK with a willingness to travel as necessary. In certain cases, we can consider sponsorship, and this will be assessed on a case-by-case basis. You will live in, or within easy commuting distance of, Oxford (or be willing to relocate) and can commit to being onsite at our Oxford office, a minimum of 3 days per working week. ## Apply [Apply at Ellison Institute of Technology](https://apply.workable.com/ellison-institute-of-technology/j/6E0FD8DCF0/apply) --- Powered by [Workable](https://www.workable.com)