Lead Platform Engineer
Lorien · London · posted 39 days ago
Going rate £52,000UK median
Occupation
2124Electronics engineers (professional)
Going rate for this occupation: £52,000 · UK median pay £52,518
Home Office going rates from
Where this salary sits
- UK pay for this occupation
- This role£49,028 to £58,034estimated · above the range ONS published
- Going rate£52,000
- UK median£52,518
View these figures as a table
| Percentile | Pay |
|---|---|
| 25th | £44,943 |
| 50th | £52,518 |
| Going rate | £52,000 |
| UK median | £52,518 |
Sponsorship
Sponsorship chance
Not derived. We hold too little to place this role on the scale.
We hold too little public record data about this employer, occupation and salary to say anything about sponsorship for this role.
- A recruitment agency posted this advert, so the employer who would hold the licence is not named.
- The salary is an estimate from national earnings data, not the employer's figure.
Why
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Lead Platform Engineer
Building the platforms that make AI and machine learning work in production
We're looking for a Lead Platform Engineer to join a growing engineering organisation and play a pivotal role in designing, building, and operating an MLOps platform that enables AI and data science teams to deliver reliably in production.
This is a senior, hands-on technical leadership role , not a people-management position. You'll lead through technical depth, judgement, and delivery , building the tooling, workflows, and operational foundations that allow data scientists and ML engineers to experiment, deploy, and run ML and LLM-based workloads safely and at scale .
The focus is not simply on running Kubernetes clusters - it's on layering real MLOps capability on top of Kubernetes to create a platform that is usable, supportable, and trusted in live environments.
What you'll be doing
You'll act as a technical leader across platform engineering, DevOps, and MLOps, remaining deeply involved in implementation.
You will:
Provide technical leadership across platform, DevOps, and MLOps activities Design, build, and operate a Kubernetes-based MLOps platform supporting the full model lifecycle ImplementandrunMLOps tooling that enables teams to:
Experiment with models and notebooks Package, version, and deploy models Run scalable inference and LLM-based workloads
Build and operate model serving and inference platforms within Kubernetes environments Work closely with data scientists and ML engineers to ensure the platform is usable, well-documented, and aligned to real workflows Own platform operability, reliability, security, and supportability in production Troubleshoot complex issues across Kubernetes, platform services, and MLOps layers Contribute to architectural decisions while staying hands-on with delivery Apply pragmatic engineering judgement in environments where AI workloads place real operational demands on infrastructure
What we're looking for
This role suits someone who is fundamentally a strong platform engineer , with the depth to apply those skills confidently to MLOps.
Essential experience:
Strong background as a Senior or Lead Platform Engineer / DevOps Engineer Deep, hands-on experience building and operating Kubernetes-based platforms Strong practical experience with Helm and Infrastructure as Code (e.g. Terraform) Proven experience extending Kubernetes with higher-level platforms and services , not treating it as the finished product Strong understanding of operational fundamentals: monitoring, logging, incident response, reliability, and maintenance Comfortable working directly with engineers and data scientists to support real production workloads
Information from public records, not immigration advice.