Senior ML Infra Engineer: Scale GPU Clusters & Pipelines

Ellison Institute, LLC; Oxford; Hybrid; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Competitive salary

25 days annual leave + 8 bank holidays

3 additional days between Christmas &.

Pension - Employer contribution 7.5%

Life Assurance

Income Protection

Private Medical Insurance for you and/

Employee discounts

Electric car scheme

Nursery Salary Sacrifice scheme

Cycle to Work Scheme

Family Planning

Neurodiversity support

Coaching & Therapy services

Job summary

Ellison Institute, LLC is seeking an experienced Senior ML infrastructure engineer to build and operate scalable GPU training and inference clusters in a secure, observable environment. You will design high-throughput data paths and manage lifecycle of compute and storage resources to accelerate research outcomes.

Ideal candidates bring hands-on experience with containerised ML pipelines, GPUs, and modern CI/CD practices.

Qualifications

• Proven experience leading the design, build, and operation of high-performance ML compute clusters at scale.
• Autonomous approach to systems design with ability to ideate, co-create and implement optimal solutions.
• Experience migrating 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.

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 Lustre).
• 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.

Skills

ML compute clusters

Systems design

Containerised infra

GPU networking

CI/CD (Terraform, Argo CD)

Tools

Kubernetes

Terraform

Argo CD

Job description

Ellison Institute, LLC is seeking an experienced Senior ML infrastructure engineer to build and operate scalable GPU training and inference clusters in a secure, observable environment. You will design high-throughput data paths and manage lifecycle of compute and storage resources to accelerate research outcomes.

Ideal candidates bring hands-on experience with containerised ML pipelines, GPUs, and modern CI/CD practices.