MLOps Engineer

Harnham - Data & Analytics Recruitment; City Of London; Hybrid; GBP 75,000 - 95,000; Full time

Benefits offered by this job

Bonus

Benefits

Job summary

Harnham is seeking a Senior MLOps Engineer in London. You will own the MLOps infrastructure powering an AI platform, work across ML, NLP and emerging AI tech to build scalable systems that deliver real-world impact.

The role focuses on building pipelines with Dagster, Airflow or Prefect, deploying ML workloads on Kubernetes and cloud, implementing CI/CD and observability, and creating IaC with Terraform or Bicep while collaborating with Data Scientists and ML engineers.

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 powering 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

Workflow orchestration

CI/CD

NLP/AI systems

Tools

Dagster

Airflow

Prefect

Terraform

Bicep

Job description

Senior MLOps Engineer

London (Hybrid) £75,000 - £95,000 + 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.