MLOps Engineer

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

Job summary

Harnham - Data & Analytics Recruitment in London is seeking a Senior MLOps Engineer to own the infrastructure powering an AI platform. You will build scalable MLOps pipelines and deploy workloads on Kubernetes and cloud platforms.

Collaborate with data scientists and ML engineers to scale deployments, implement CI/CD, observability, and IaC using Terraform or similar tools. Hybrid work arrangement in London.

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

Workflow orchestration

IaC/CI-CD

Production ML/NLP/AI

Tools

Dagster

Airflow

Prefect

Job description

Senior MLOps Engineer

London (Hybrid) £75,000 - £85,000 + Bonus + BenefitsThis 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.