Senior Quality Cloud Engineer (MLOps Engineer)

ClearRoute; London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading engineering consultancy, ClearRoute, seeks a Senior Quality Cloud Engineer (MLOps Engineer) to enhance their cloud offerings. The role involves deploying and managing ML models in Azure while collaborating with diverse teams. Ideal candidates bring extensive experience in Azure tools and MLOps best practices. Join ClearRoute to influence change and shape the future of consultancy in a supportive environment.

Qualifications

• 3+ years of experience in MLOps or DevOps.
• Strong expertise in Azure AI and DevOps tools.
• Proficiency in Python and ML libraries/frameworks.

Responsibilities

• Design and maintain scalable ML pipelines using Azure services.
• Implement CI/CD for ML workflows and manage model deployments.
• Collaborate with teams to ensure model integration into production.

Skills

MLOps

Azure AI tools

DevOps

Python

Containerization

Tools

Azure Kubernetes Service (AKS)

Azure Machine Learning

Azure DevOps

Azure Data Factory

Docker

Terraform

Job description

About us:

We are an engineering consultancy bridging Quality Engineering, Cloud Platforms and Developer Experience.

Our values challenge us to do the best we can for ClearRoute, our customers and most importantly our team. We want to create a collaborative team to help build ClearRoute. This is an opportunity for you to build a consultancy from the ground up, use your voice to drive change and help transform organisations and problem domains.

Role:

We are looking for a skilled Senior Quality Cloud Engineer (MLOps Engineer) with expertise in Microsoft Azure to join our team. In this role, you will play a pivotal part in deploying, managing, and scaling machine learning models to ensure seamless integration into our production environment. The ideal candidate has hands-on experience with Azure's suite of AI and DevOps tools, coupled with a deep understanding of MLOps best practices.

Key Responsibilities

• Design, build, and maintain scalable and secure ML pipelines using Azure Machine Learning (AML) services.
• Implement CI/CD pipelines for ML workflows using Azure DevOps or GitHub Actions.
• Manage and monitor model deployment, versioning, and lifecycle using Azure Model Registry.
• Ensure data and model governance, including compliance with security and privacy standards.
• Optimize compute resources in Azure, leveraging tools such as Azure Kubernetes Service (AKS) and Azure Batch for cost-effective scaling.
• Collaborate with data scientists, engineers, and product teams to integrate ML solutions into production systems.
• Implement monitoring and logging solutions to track model performance and identify drift or anomalies in production.
• Automate data preprocessing and feature engineering workflows using Azure Data Factory or Databricks.
• Drive the adoption of MLOps best practices within the organization.

Required Qualifications

• 3+ years of experience in MLOps, DevOps, or a related role.

• Strong expertise with Azure AI and DevOps tools, including; Azure Machine Learning, Azure DevOps, Azure Kubernetes Service (AKS), Azure Data Factory, Azure Storage and Data Lake
• Proficiency in Python and libraries/frameworks commonly used in machine learning (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with containerisation and orchestration tools like Docker and Kubernetes.
• Familiarity with Infrastructure-as-Code (IaC) tools such as Terraform or Bicep for Azure resource management.
• Solid understanding of CI/CD pipelines, version control systems (e.g., Git), and automated testing.
• Knowledge of monitoring tools such as Azure Monitor or Prometheus for tracking ML pipeline health.

What Next?

ClearRoute is committed to creating an inclusive working environment where people can be themselves at work. We celebrate individuality and our differences. We understand that some differences may mean that you require changes made to the interview process. We are happy to cater to your needs to make the interview accessible, please let us know by emailing us at [e-mail].

If you see yourself taking on this exciting new opportunity, just click the 'Apply Now’ button and submit your CV.