Senior ML Ops Engineer

Senior MLOps Engineer

£75,000 - £85,000

London (1-2 days a week in office)

This is an opportunity to join a growing AI and data-driven organisation where your work will have a direct impact on the development and delivery of advanced machine learning solutions. You will play a key role in shaping scalable MLOps infrastructure, enabling AI products to operate reliably across a diverse client base while contributing to meaningful, real-world outcomes.

THE COMPANY

They are a mission-led technology business that uses data, machine learning, and advanced analytics to help organisations make better decisions. Their platform combines data engineering, AI, and predictive modelling to generate actionable insights at scale. As they continue to grow, they are investing heavily in their AI capabilities and platform infrastructure, creating an exciting environment for engineers who enjoy solving complex technical challenges.

THE ROLE

As a Senior MLOps Engineer, you will join the platform engineering function, owning and evolving the infrastructure that underpins the organisation's AI services

Specifically, you can expect to be involved in the following:

• Designing and maintaining scalable MLOps infrastructure that supports machine learning, NLP, knowledge representation, and AI applications.
• Deploying and managing machine learning models using Azure ML, Azure Kubernetes Service (AKS), and associated cloud technologies.
• Building and maintaining production-grade orchestration pipelines for model training, inference, monitoring, and retraining.
• Developing CI/CD pipelines to automate testing, deployment, and operational processes.
• Implementing observability, monitoring, and alerting frameworks to ensure platform reliability and performance.
• Driving best practice around Responsible AI, governance, transparency, and auditability.
• Collaborating with engineering, delivery, and consulting teams to support the adoption and scaling of AI solutions
• Other key responsibilities & selling points of role.

SKILLS AND EXPERIENCE

The successful Senior MLOps Engineer will have the following skills and experience:

• Strong commercial experience in MLOps, platform engineering, infrastructure engineering, or a related field.
• Advanced Python development skills within production environments.
• Expertise with Azure-native MLOps tools, including model endpoints, pipelines, registries, environments, and compute resources.
• Experience deploying and supporting containerised workloads on Kubernetes.
• Strong knowledge of CI/CD practices using Azure DevOps or similar tooling.
• Experience with infrastructure-as-code technologies such as Terraform, Bicep, or Pulumi.
• Knowledge of monitoring and observability tooling such as Prometheus and Grafana.
• Experience with orchestration platforms including Dagster, Airflow, Prefect, or similar.

BENEFITS

The successful Senior MLOps Engineer will receive the following benefits:

• Salary between £75,000 - £85,000 - depending on experience

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