ForGood
Home / Jobs /Engineering & Technology / Senior ML Infrastructure Engineer
EI
Ellison Institute of Technology

Senior ML Infrastructure Engineer

LocationOxford, England, United Kingdom (remote friendly)
SetupRemote
LevelSenior
Posted22h ago
Apply by2026-12-31
Engineering & Technology

Quick answer

Ellison Institute of Technology is hiring a remote-friendly Senior ML Infrastructure Engineer (Oxford, England, United Kingdom) with a competitive salary and benefits to build and operate high-performance ML compute clusters.

Role
Senior ML Infrastructure Engineer
Organization
Ellison Institute of Technology
Location
Oxford, England, United Kingdom (remote friendly)
Work setup
Remote
Level
Senior
Compensation
Competitive salary (dependent on experience) + travel allowance + bonus
Category
Engineering & Technology
Apply by
2026-12-31

The 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.

What you'll do

  • Build, operate, and continuously optimise our high-performance GPU training and inference clusters
  • Drive systems design and implementation for high-throughput data paths
  • Proactively benchmark, profile, and resolve performance bottlenecks
  • Establish comprehensive observability, resilience, and automated security controls
  • Partner with Research, Data, and Applied teams to forecast capacity and cost for GPU and storage needs

What it takes

  • Proven experience leading the design, build, and operation of high-performance ML compute clusters at scale
  • 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 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
  • Expert-level understanding of IaC and CI/CD practices (e.g., Terraform, Argo CD)

What you'll bring

Proven experience leading the designbuildand operation of high-performance ML compute clusters at scaleExpertise with high-throughput storage systems for ML/HPC workloadsExpert-level understanding of GPU architecturehigh-speed networking for distributed training

How we treat you

Enhanced holiday, Pension - Employer contribution 7.5%, minimum employee contribution 5%, Life Assurance, Income Protection, Private Medical Insurance as standard, Employee discounts, Electric car scheme, Nursery Salary Sacrifice scheme, Cycle to Work Scheme, Family Planning, Neurodiversity support, Coaching & Therapy services

Frequently asked questions

Where is the job located?

The job is located in Oxford, England, United Kingdom, but it is remote-friendly.

What is the compensation?

The compensation is a competitive salary (dependent on experience) + travel allowance + bonus.

What are the key qualifications required?

Key qualifications include proven experience leading the design, build, and operation of high-performance ML compute clusters at scale, expertise with high-throughput storage systems for ML/HPC workloads, and expert-level understanding of GPU architecture, high-speed networking for distributed training, and performance profiling to resolve bottlenecks.

How do I apply?

You can apply now by visiting the Ellison Institute of Technology's job posting page.

How to apply

Apply directly on Ellison Institute of Technology's site. We link straight through — no resume parsing, no profile to fill out.

Apply now →

This listing is aggregated from a third-party source and its summary may be auto-generated, so details can be inaccurate or out of date. ForGood is not the employer and is not liable for the content — please verify everything on Ellison Institute of Technology's official posting before applying.