Senior ML Ops Engineer

Harnham - Data and Analytics Recruitment; Greater London; Hybrid; GBP 75,000 - 85,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Harnham - Data and Analytics Recruitment is seeking a Senior MLOps Engineer in London. You will join the platform engineering team to shape scalable MLOps infrastructure supporting AI services for diverse clients.

Key responsibilities include deploying ML models with Azure ML and AKS, building robust CI/CD pipelines, and driving observability and governance to ensure reliable, responsible AI delivery.

Qualifications

• High-level experience in MLOps and platform engineering across production environments.
• Advanced Python development skills in production systems.
• Expertise with Azure-native MLOps tools including endpoints, pipelines, registries, environments and compute.
• Experience deploying containerised workloads on Kubernetes.
• Strong knowledge of CI/CD practices using Azure DevOps or similar tooling.
• Experience with Terraform, Bicep or Pulumi for IaC.
• Knowledge of monitoring/observability tooling (Prometheus, Grafana).
• Experience with orchestration platforms like Dagster, Airflow, Prefect or similar.

Responsibilities

• Own and evolve scalable MLOps infrastructure underpinning AI services.
• Deploy and manage ML models using Azure ML and AKS.
• Build production-grade pipelines for training, inference, monitoring, and retraining.
• Develop CI/CD pipelines to automate testing, deployment, and operations.
• Implement observability, monitoring, and alerting for reliability.
• Drive responsible AI, governance, transparency and auditability.
• Collaborate with engineering, delivery and consulting teams to scale AI solutions.

Skills

MLOps

Python

Azure ML/AKS

Kubernetes

CI/CD (Azure DevOps)

Infra as Code (Terraform/Bicep/Pulumi)

Monitoring (Prometheus/Grafana)

Workflow orchestration (Dagster/Airlfy

Tools

Dagster

Airflow

Prefect

Job description

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