MLOps Engineer

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

Benefits offered by this job

Bonus

Benefits

Job summary

Harnham - Data and Analytics Recruitment in London is seeking a Senior MLOps Engineer to own the infrastructure powering an expanding AI platform. The role combines hands-on development with production ML, NLP, and scalable systems that deliver real-world impact.

You will deploy ML workloads on Kubernetes and cloud platforms, implement CI/CD and observability, and work closely with data scientists and AI teams to scale deployments in a hybrid London environment.

Qualifications

• Strong Python software engineering skills.
• Commercial MLOps experience in production environments.
• Hands-on Kubernetes expertise.
• Experience with workflow orchestration platforms.
• Infrastructure as Code and CI/CD experience.
• Understanding of production ML, NLP, or AI systems.

Responsibilities

• Own and develop the MLOps infrastructure supporting AI services.
• Build and maintain orchestration pipelines using Dagster, Airflow, or Prefect.
• Deploy and manage ML workloads on Kubernetes and cloud platforms.
• Implement CI/CD, observability, and monitoring across production systems.
• Develop infrastructure using Terraform, Bicep, or similar IaC tools.
• Work closely with Data Scientists, ML Engineers, and AI teams to scale deployments.

Skills

Python

MLOps

Kubernetes

CI/CD pipelines

Workflow orchestration

Production ML/NLP/AI systems

Tools

Dagster

Airflow

Prefect

Terraform

Bicep

Kubernetes

Job description

Senior MLOps Engineer
London (Hybrid) | £75,000 - £85,000 + Bonus + Benefits

This is an opportunity to take ownership of the infrastructure powering a growing AI platform. You'll work across machine learning, NLP, and emerging AI technologies, helping build scalable systems that support real-world impact.

The Company

A growing AI and data consultancy helping organisations use data and machine learning to improve decision-making and deliver better outcomes. They are investing heavily in their AI platform and expanding their engineering capability.

The Role

• Own and develop the MLOps infrastructure supporting AI services.
• Build and maintain orchestration pipelines using Dagster, Airflow, or Prefect.
• Deploy and manage ML workloads on Kubernetes and cloud platforms.
• Implement CI/CD, observability, and monitoring across production systems.
• Develop infrastructure using Terraform, Bicep, or similar IaC tools.
• Work closely with Data Scientists, ML Engineers, and AI teams to scale deployments.

Your Skills & Experience

• Strong Python software engineering skills.
• Commercial MLOps experience in production environments.
• Hands-on Kubernetes expertise.
• Experience with workflow orchestration platforms.
• Infrastructure as Code and CI/CD experience.
• Understanding of production ML, NLP, or AI systems.