Senior MLOps Engineer
Not disclosed
Salary
Not disclosed by employer
£41,700
Going rate
Skilled Worker going rate
This role may qualify for a Skilled Worker visa
SOC 5242 is an eligible occupation, but we classified this role with low confidence (42% match). If the code is right — and GIOS Technology is a licensed sponsor — it should qualify, but double-check the occupation eligibility rules against the actual role.
About the role
We are looking for Senior MLOps Engineer at London, UK – 3 days per week Onsite
Role Overview
We are seeking an experienced Senior MLOps Engineer to support the design, implementation, and optimisation of enterprise-scale MLOps platforms on Microsoft Azure. Working closely with Solution and Enterprise Architects, the successful candidate will help build and operate scalable machine learning platforms on Kubernetes, with a focus on model lifecycle management, observability, low-latency inference, platform reliability, and cost efficiency.
Key Responsibilities
- Partner with Architects to design and implement end-to-end MLOps solutions on Azure.
- Build and operate scalable ML platforms using Azure Kubernetes Service (AKS) and cloud-native technologies.
- Develop CI/CD and Continuous Training (CT) pipelines for machine learning workloads.
- Deploy, manage, and optimise ML workloads in Kubernetes environments.
- Implement model serving capabilities that meet high-availability and low-latency requirements.
- Configure autoscaling, traffic management, rollback strategies, and resource governance.
- Manage containerised ML applications using Docker, Kubernetes, Helm, and GitOps practices.
- Implement monitoring and observability across:
- Model performance and drift
- Application performance and platform health
- Infrastructure and operational metrics
- Leverage Azure services including Azure Machine Learning, AKS, Azure Monitor, Application Insights, and Azure DevOps/GitHub Actions.
Performance & Cost Optimisation
- Optimise cloud infrastructure utilisation and spend for ML workloads.
- Implement efficient compute and scaling strategies across training and inference environments.
- Drive FinOps practices, cost visibility, and resource right-sizing.
- Improve platform performance, reliability, throughput, and latency.
Required Skills & Experience
- 8+ years' experience in Software Engineering, Platform Engineering, DevOps, or MLOps.
- 5+ years' experience building and operating production MLOps platforms.
- Strong hands-on experience with Azure-based MLOps architectures and AKS.
- Deep expertise in Kubernetes, containerisation, and model deployment patterns.
- Experience implementing monitoring, observability, and model lifecycle management.
- Hands-on experience with CI/CD pipelines and Infrastructure as Code.
- Experience with Azure Monitor, Application Insights, Azure DevOps, and/or GitHub Actions.
- Proficiency with Terraform, Bicep, or equivalent.
- Strong Python and scripting skills.
- Experience supporting low-latency ML inference workloads and cloud cost optimisation initiatives.
This description is the source posting as it read when we added it. We are not affiliated with GIOS Technology, so check their own site for the current details.
Where this offer sits in the market
SOC 5242 · UK · ONS ASHE 2025 · ~24k in sampleSimilar sponsored roles
See all jobsNo close matches live right now.
Browse more sponsored jobs at GIOS TechnologyAbout sponsorship for this role
Does this job guarantee visa sponsorship?
Not necessarily. GIOS Technology holds a sponsor licence, but sponsorship for a specific hire is always the employer's decision. Be upfront in your application that you'll require it.
What salary is needed for this role to be eligible?
The offer must clear both the general threshold and the SOC 5242 going rate of £41,700. New-entrant and shortage discounts can lower it.