Senior MLOps Engineer

Ref: BBBH67814_1786442313

Senior MLOps Engineer

Whitehall Resources currently require an experienced Senior MLOps Engineer to work with a key client.

**Please note this role falls INSIDE IR35**
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.

All of our opportunities require that applicants are eligible to work in the specified country/location, unless otherwise stated in the job description.

Whitehall Resources are an equal opportunities employer who value a diverse and inclusive working environment. All qualified applicants will receive consideration for employment without regard to race, religion, gender identity or expression, sexual orientation, national origin, pregnancy, disability, age, veteran status, or other characteristics.

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