workable
Senior ML Infrastructure Engineer
Ellison Institute of Technology
Oxford, GBR
Full-time
Senior
Hybrid
Discovered 1 weeks ago
LustreTerraformArgo CDIaCCI/CDGPU
Free
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LustreTerraformArgo CDIaCCI/CDGPU
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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 www.eit.org
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.
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